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Borges LN, Fernandes EAF, Oliveira ÉMD, Pereira VG, Diniz A. Experiences and initiatives on pharmacokinetic modeling and simulation data analysis: Perspectives from the Brazilian Health Regulatory Agency (ANVISA). Regul Toxicol Pharmacol 2024; 154:105728. [PMID: 39442666 DOI: 10.1016/j.yrtph.2024.105728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 10/13/2024] [Accepted: 10/19/2024] [Indexed: 10/25/2024]
Abstract
The landscape of drug product development and regulatory sciences is evolving, driven by the increasing application of systems thinking and modeling and simulation (M&S) techniques, especially from a biopharmaceutics perspective. Patient-centric quality standards can be achieved within this context through the application of quality by design (QbD) principles and M&S, specifically by defining clinically relevant dissolution specifications (CRDS). To this end, it is essential to bridge in vitro results to drug product in vivo performance, emphasizing the need to explore the translational capacity of biopharmaceutics tools. Physiologically based M&S analyses offer a unique avenue for integrating the drug, drug product, and biological properties of a target organism to study their interactions on the pharmacokinetic response. Accordingly, Physiologically Based Biopharmaceutics Modeling (PBBM) has seen increasing use to support drug development and regulatory applications globally. In Brazil, a Model-Informed Drug Development (MIDD) policy and strategic project are not yet established, limiting applicability of M&S techniques. Drawing from the experience of the ANVISA-Academia PBBM Working Group (WG), this article assesses the opportunities and challenges for pharmacometrics (PMx) in Brazil and proposes strategies to advance the adoption of M&S analyses into regulatory decision-making.
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Affiliation(s)
- Luiza Novaes Borges
- Pharmacokinetics and Biopharmaceutics Laboratory (PKBio), Department of Pharmacy, State University of Maringá, PR, Brazil; Brazilian Health Regulatory Agency (ANVISA), Division of Therapeutic Equivalence (CETER), Brasília, Brazil.
| | | | - Érico Miroro de Oliveira
- Brazilian Health Regulatory Agency (ANVISA), Office of Synthetic Medicines Quality Assessment (GQMED), Brasília, Brazil.
| | - Victor Gomes Pereira
- Brazilian Health Regulatory Agency (ANVISA), Office of Synthetic Medicines Quality Assessment (GQMED), Brasília, Brazil.
| | - Andréa Diniz
- Pharmacokinetics and Biopharmaceutics Laboratory (PKBio), Department of Pharmacy, State University of Maringá, PR, Brazil.
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2
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Alasmari MS, Albusaysi S, Elhefnawy M, Ali AM, Altigani K, Almoslem M, Alharbi M, Alghamdi J, Alsultan A. Model-informed drug discovery and development approaches to inform clinical trial design and regulatory decisions: A primer for the MENA region. Saudi Pharm J 2024; 32:102207. [PMID: 39697476 PMCID: PMC11653594 DOI: 10.1016/j.jsps.2024.102207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Accepted: 11/19/2024] [Indexed: 12/20/2024] Open
Abstract
Model-Informed Drug Discovery and Development (MID3) represents a transformative approach in pharmaceutical research, integrating quantitative models to inform and optimize decision-making throughout the drug development process. This review explores the current applications, challenges, and future prospects of MID3 within the Middle East and North Africa (MENA) region. By leveraging local data and advanced computational techniques, MID3 has the potential to significantly enhance the efficiency and success rates of drug development tailored to regional health priorities. We discussed successful case studies of applying MID3 at different phases of drug development and clinical trials. Furthermore, we emphasized the critical need for MENA countries to embrace MID3 by investing in workforce training, aligning regulatory frameworks, and fostering collaborative research initiatives. This call to action underscores the importance of a robust MID3 ecosystem, urging policymakers, academic institutions, and industry stakeholders to prioritize and support its integration into the MENA region's healthcare.
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Affiliation(s)
- Mohammed S. Alasmari
- Department of Pharmaceutical Services, Security Forces Hospital, Riyadh 11481, Saudi Arabia
| | - Salwa Albusaysi
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | | | | | - Khalid Altigani
- Department of Clinical Pharmacy, College of Pharmacy, Najran University, Saudi Arabia
| | | | | | | | - Abdullah Alsultan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia
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3
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Krumpholz L, Polak S, Wiśniowska B. Physiologically-based pharmacokinetic model of in vitro porcine ear skin permeation for drug delivery research. J Appl Toxicol 2024; 44:1936-1948. [PMID: 39134399 DOI: 10.1002/jat.4687] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 08/01/2024] [Accepted: 08/01/2024] [Indexed: 11/09/2024]
Abstract
In silico techniques, such as physiologically based pharmacokinetic modeling (PBKP), are recently gaining importance. Computational methods in drug discovery and development and the generic drugs industry enhance research effectiveness by saving time and money and avoiding ethical issues. One key advantage is the ability to conduct toxicology studies without risking harm to living beings. This study aimed to repurpose the multi-phase multi-layer mechanistic dermal absorption (MPML MechDermA) PBPK model for simulation permeation through porcine ear skin under in vitro conditions. The work was divided into four steps: (1) the development of a pig ear skin model based on a previously collected dataset; (2) testing the model's ability to discriminate permeation between pig ear, human abdomen, and human back skin; (3) development of a caffeine permeation model; and (4) testing the caffeine model's performance against in vitro generated data sourced from the scientific literature. Data from 31 manuscripts were used for the development of the pig skin model. Based on these data, values specific to pig skin were found for 22 parameters of the MPML MechDermA model. The model was able to discriminate permeation between pig and human skin. A caffeine model was developed and used to simulate seven experiments identified in the literature. The model's performance was assessed by comparing simulated to observed results. Based on a visual check, all simulations were considered acceptable, whereas three out of seven experiments met the twofold difference criterion. The variability of the experimental data was considered the biggest challenge for reliable model assessment.
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Affiliation(s)
- Laura Krumpholz
- Pharmacoepidemiology and Pharmacoeconomics Unit, Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland
- Doctoral School in Medical and Health Sciences, Jagiellonian University Medical College, Kraków, Poland
| | - Sebastian Polak
- Chair of Pharmaceutical Technology and Biopharmaceutics, Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland
- Certara UK Ltd. (Simcyp Division), Sheffield, UK
| | - Barbara Wiśniowska
- Pharmacoepidemiology and Pharmacoeconomics Unit, Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland
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4
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Cilliers C, Howgate E, Jones HM, Rahbaek L, Tran JQ. Clinical and Physiologically Based Pharmacokinetic Model Evaluations of Adagrasib Drug-Drug Interactions. Clin Pharmacol Ther 2024. [PMID: 39587812 DOI: 10.1002/cpt.3506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2024] [Accepted: 11/10/2024] [Indexed: 11/27/2024]
Abstract
Adagrasib is a potent, highly selective, orally available, small molecule, covalent inhibitor of G12C mutated KRAS. As both a substrate and strong inhibitor of cytochrome P450 (CYP) 3A4, adagrasib inhibits its own CYP3A4-mediated metabolism following multiple dosing, resulting in time-dependent drug-drug interaction (DDI) liabilities. A physiologically-based pharmacokinetic (PBPK) model was developed and verified using a combination of physicochemical, in vitro and clinical pharmacokinetic (PK) data from healthy volunteers and cancer patients. The PBPK model well-described the single and multiple-dose adagrasib PK data as well as DDI data with itraconazole, rifampin, midazolam, warfarin, dextromethorphan, and digoxin, with model predictions within 1.5-fold of the observed clinical data. The PBPK model was used to predict untested scenarios including the clinical victim and perpetrator DDI liabilities at the approved dosing regimen of 600 mg twice daily (b.i.d.) in cancer patients. Strong, moderate, and weak inhibitors of CYP3A4 are predicted to have a negligible effect on the steady-state exposure of adagrasib 600 mg b.i.d. resulting from the significant inactivation of CYP3A4 by adagrasib. Additionally, strong and moderate inducers of CYP3A4 are predicted to decrease adagrasib exposure by 68% and 22%, respectively. As a perpetrator, adagrasib 600 mg b.i.d. is predicted to be a strong inhibitor of CYP3A4, a moderate inhibitor of CYP2C9 and CYP2D6, and an inhibitor of P-glycoprotein (P-gp). These results successfully supported regulatory interactions with the United States Food and Drug Administration regarding dosing recommendations for when adagrasib is used concomitantly with other medications, supporting a range of label claims in lieu of clinical trials.
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Affiliation(s)
- Cornelius Cilliers
- Clinical Pharmacology and Nonclinical Development, Mirati Therapeutics Inc. (A Bristol Myers Squib Company), San Diego, California, USA
| | | | | | - Lisa Rahbaek
- Clinical Pharmacology and Nonclinical Development, Mirati Therapeutics Inc. (A Bristol Myers Squib Company), San Diego, California, USA
| | - Jonathan Q Tran
- Clinical Pharmacology and Nonclinical Development, Mirati Therapeutics Inc. (A Bristol Myers Squib Company), San Diego, California, USA
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5
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Zhao Y, Yin N, Yang R, Faiola F. Recent advances in environmental toxicology: Exploring gene editing, organ-on-a-chip, chimeric animals, and in silico models. Food Chem Toxicol 2024; 193:115022. [PMID: 39326696 DOI: 10.1016/j.fct.2024.115022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 09/05/2024] [Accepted: 09/22/2024] [Indexed: 09/28/2024]
Abstract
In our daily life, we are exposed to various environmental pollutants in multiple ways. At present, we mainly rely on animal models and two-dimensional cell culture models to evaluate the toxicity of environmental pollutants. Nevertheless, results in animal models do not always apply to humans because of differences between species, while two-dimensional cell culture models cannot replicate the in vivo microenvironments, making it difficult to predict the true toxic response of environmental pollutants in humans. The development of various high-end technologies in recent years has provided new opportunities for environmental toxicology research. The application of these high-end technologies in environmental toxicology can complement the limitations of traditional environmental toxicology screening and more accurately predict the toxicity of environmental pollutants. In this review, we first introduce the advantages and disadvantages of traditional environmental toxicology methods, then review the principles and development of four high-end technologies, such as gene editing, organ-on-a-chip, chimeric animals, and in silico models, summarize their application in toxicity testing, and finally emphasize their importance/potential in environmental toxicology.
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Affiliation(s)
- Yanyi Zhao
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Nuoya Yin
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Renjun Yang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Francesco Faiola
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
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6
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Kikuchi R, Qian Y, Badawi M, Savaryn JP, Gannu S, Eldred A, Hao S, Salem AH, Liu W, Klein CE, Mohamed MEF. Coproporphyrin-I as a Selective OATP1B Biomarker Can Be Used to Delineate the Mechanisms of Complex Drug-Drug Interactions: Cedirogant Case Study. Clin Pharmacol Ther 2024; 116:1334-1342. [PMID: 39102854 DOI: 10.1002/cpt.3399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 07/16/2024] [Indexed: 08/07/2024]
Abstract
Cedirogant is an inverse agonist of retinoic acid-related orphan receptor gamma thymus developed for the treatment of chronic plaque psoriasis. Cedirogant induces cytochrome P450 (CYP) 3A4 while inhibiting P-glycoprotein (P-gp), breast cancer resistance protein (BCRP), organic anion transporting polypeptide (OATP) 1B1, and OATP1B3 in vitro. Static drug-drug interactions (DDIs) predictions suggested possible clinical induction of CYP3A4, and inhibition of P-gp, BCRP, and OATP1B1, leading to challenges in interpreting DDI studies between cedirogant and substrates of CYP3A, P-gp, BCRP, and OATP1B1/3. Here the effects of cedirogant on the pharmacokinetics of two statin drugs were investigated in healthy participants. Coproporphyrin-I (CP-I), a selective endogenous OATP1B biomarker, was used to assess the impact of cedirogant on OATP1B. Cedirogant (375 mg once daily) increased rosuvastatin maximum plasma concentration (Cmax) and area under the plasma concentration curve (AUCtau) by 141% and 55%, respectively when co-administered, whereas atorvastatin Cmax increased by 40% with no effect on its AUCtau compared with administration of rosuvastatin/atorvastatin alone. Cedirogant did not increase CP-I exposures, indicating no clinical OATP1B inhibition. The increased rosuvastatin exposure and minimal change in atorvastatin exposure with co-administration of cedirogant is attributed to BCRP inhibition and interplay between P-gp/BCRP inhibition and CYP3A induction, respectively. Correlation analysis with data from two investigational drugs (glecaprevir and flubentylosin) demonstrated that OATP1B1 R-value of > 1.5 and [Cmax,u]/[OATP1B1 IC50] of > 0.1 are associated with > 1.25-fold increase in CP-I Cmax ratio. This demonstrates the utility of CP-I in disentangling mechanisms underlying a complex DDI involving multiple transporters and enzymes and proposes refined criteria for static OATP1B inhibition predictions.
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Affiliation(s)
- Ryota Kikuchi
- Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois, USA
| | - Yuli Qian
- Clinical Pharmacology, AbbVie Inc., North Chicago, Illinois, USA
| | - Mohamed Badawi
- Clinical Pharmacology, AbbVie Inc., North Chicago, Illinois, USA
| | - John P Savaryn
- Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois, USA
| | - Shashikanth Gannu
- Quantitative, Translational and ADME Sciences, AbbVie Inc., North Chicago, Illinois, USA
| | - Ann Eldred
- Immunology Development, AbbVie Inc., North Chicago, Illinois, USA
| | - Shuai Hao
- Discovery and Exploratory Statistics, AbbVie Inc., North Chicago, Illinois, USA
| | - Ahmed Hamed Salem
- Clinical Pharmacology, AbbVie Inc., North Chicago, Illinois, USA
- Clinical Pharmacy, Ain Shams University, Cairo, Egypt
| | - Wei Liu
- Clinical Pharmacology, AbbVie Inc., North Chicago, Illinois, USA
| | - Cheri E Klein
- Clinical Pharmacology, AbbVie Inc., North Chicago, Illinois, USA
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7
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Cole S, Malamatari M, Butler A, Arshad M, Kerwash E. Investigation of a fully mechanistic physiologically based pharmacokinetics model of absorption to support predictions of milk concentrations in breastfeeding women and the exposure of infants: A case study for albendazole. CPT Pharmacometrics Syst Pharmacol 2024; 13:1990-2001. [PMID: 39558864 DOI: 10.1002/psp4.13260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 09/18/2024] [Accepted: 10/07/2024] [Indexed: 11/20/2024] Open
Abstract
Due to limited non-clinical and clinical data, European guidance recommends to discontinue breastfeeding when taking albendazole. The aim of this study was to consider the use of PBPK modeling to support the expected exposure in breastfed infants. A fully mechanistic PBPK approach was used to provide quantitative predictions of albendazole and its main active metabolite, albendazole sulfoxide, concentrations in plasma and breast milk of lactating women. The model predicted the exposure in adults and the large food effect, however, it does not predict all the clinical data for the exposure in children. Milk/plasma ratio predictions were also largely over-predicted for this lipophilic compound, but not for the less lipophilic metabolite. Predictions using the observed ratio and a worse-case exposure based on Cmax predictions, suggest doses to children through milk will be low. However, more clinical data are required before full exposure predictions can be made to breastfed infants.
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Affiliation(s)
- Susan Cole
- Medicines and Healthcare Products Regulatory Agency, London, UK
| | | | - Andrew Butler
- Medicines and Healthcare Products Regulatory Agency, London, UK
| | | | - Essam Kerwash
- Medicines and Healthcare Products Regulatory Agency, London, UK
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García MA, Paulos C, Ibarra Viñales M, Michelet R, Cabrera-Pérez MÁ, Aceituno A, Bone M, Ibacache M, Cortínez LI, Guzmán M. Modeling and Simulations in Latin-American Generic Markets: Perspectives from Chilean Local Industry, Regulatory Agency, and Academia. Mol Pharm 2024. [PMID: 39454202 DOI: 10.1021/acs.molpharmaceut.4c00764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2024]
Abstract
In the last 20 years, modeling and simulations (M&S) have gained increased attention in pharmaceutical sciences. International industry and world-reference agencies have used M&S to make cost-efficient decisions through the model-informed drug development (MIDD) framework. Modeling tools include biopredictive dissolution models, physiologically based pharmacokinetic models (PBPK), biopharmaceutic models (PBBM), and virtual bioequivalence, among many others. Regulatorily, health agencies are becoming more and more open to accept the use of M&S to support regulatory applications, including setting dissolution specifications, quality-by-design (QbD), postapproval changes (SUPAC), etc. Nonetheless, the potential of M&S has been only barely explored in Latin America (Latam) across different actors: industry, regulatory agencies, and even academia. In this manuscript, we discuss the challenges and opportunities for implementing M&S approaches in Latam. Perspectives of regional experts were shared in a workshop. Attendance (professionals from industry, regulator, academia, and clinicians) also shared their views via survey. The rational development of bioequivalent generics was considered the main opportunity for M&S in regional market, particularly the use of PBPK and PBBM. Nonetheless, a critical mass of modeling scientists is needed before Latin American industry and regulators can actually benefit from M&S. Collaborations (e.g., Academia-Industry and Academia-Regulatory) may be a path to develop applied research projects and train the future modelers. Reaching that critical mass, scientists from industry may apply modeling across generic drug development process and life cycle, while regulatory scientists may issue guidelines in local language to support regional industry. Only at that stage could the full potential of MIDD be reached in Latin American generic markets.
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Affiliation(s)
- Mauricio A García
- Departamento de Farmacia, Escuela de Química y Farmacia, Facultad de Química y de Farmacia, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| | - Claudio Paulos
- Departamento de Farmacia, Escuela de Química y Farmacia, Facultad de Química y de Farmacia, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
| | - Manuel Ibarra Viñales
- Department of Pharmaceutical Sciences, Faculty of Chemistry, Universidad de la República, Montevideo 11800, Uruguay
| | - Robin Michelet
- Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universität Berlin, Kelchstraße 31, Berlin 14195, Germany
- qPharmetra LLC, Berlin 14195, Germany
| | - Miguel Ángel Cabrera-Pérez
- Departamento de Ciencias Farmacéuticas, Facultad de Ciencias, Universidad Católica del Norte, Antofagasta 1240000, Chile
| | - Alexis Aceituno
- National Drug Agency Department, Institute of Public Health (ISP), Santiago 7780050, Chile
- University of Valparaíso, Faculty of Pharmacy, Valparaíso 2381850, Chile
| | - Michelle Bone
- National Drug Agency Department, Institute of Public Health (ISP), Santiago 7780050, Chile
| | - Mauricio Ibacache
- División Anestesiología, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago de Chile 7820436, Chile
| | - Luis Ignacio Cortínez
- División Anestesiología, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago de Chile 7820436, Chile
| | - Marcelo Guzmán
- Validations and Bioequivalence, Laboratorio Milab, Grupo FEMSA, Santiago 8380000, Chile
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Choules MP, Bonate PL, Heo N, Weddell J. Prospective approaches to gene therapy computational modeling - spotlight on viral gene therapy. J Pharmacokinet Pharmacodyn 2024; 51:399-416. [PMID: 37848637 DOI: 10.1007/s10928-023-09889-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 09/25/2023] [Indexed: 10/19/2023]
Abstract
Clinical studies have found there still exists a lack of gene therapy dose-toxicity and dose-efficacy data that causes gene therapy dose selection to remain elusive. Model informed drug development (MIDD) has become a standard tool implemented throughout the discovery, development, and approval of pharmaceutical therapies, and has the potential to inform dose-toxicity and dose-efficacy relationships to support gene therapy dose selection. Despite this potential, MIDD approaches for gene therapy remain immature and require standardization to be useful for gene therapy clinical programs. With the goal to advance MIDD approaches for gene therapy, in this review we first provide an overview of gene therapy types and how they differ from a bioanalytical, formulation, route of administration, and regulatory standpoint. With this biological and regulatory background, we propose how MIDD can be advanced for AAV-based gene therapies by utilizing physiological based pharmacokinetic modeling and quantitative systems pharmacology to holistically inform AAV and target protein dynamics following dosing. We discuss how this proposed model, allowing for in-depth exploration of AAV pharmacology, could be the key the field needs to treat these unmet disease populations.
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Affiliation(s)
- Mary P Choules
- Early Development, New Technologies Group, Astellas, Northbrook, IL, USA
| | - Peter L Bonate
- Early Development, New Technologies Group, Astellas, Northbrook, IL, USA.
| | - Nakyo Heo
- Early Development, New Technologies Group, Astellas, Northbrook, IL, USA
| | - Jared Weddell
- Early Development, New Technologies Group, Astellas, Northbrook, IL, USA
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Abla N, Marrast AC, Jambert E, Richardson N, Duparc S, Almond L, Rowland Yeo K, Pan X, Tarning J, Zhao P, Culpepper J, Waitt C, Koldeweij C, Cole S, Butler AS, Khier S, Möhrle JJ, El Gaaloul M. Addressing health equity for breastfeeding women: primaquine for Plasmodium vivax radical cure. Malar J 2024; 23:287. [PMID: 39334094 PMCID: PMC11438061 DOI: 10.1186/s12936-024-05112-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 09/13/2024] [Indexed: 09/30/2024] Open
Abstract
Plasmodium vivax malaria remains a global health challenge, with approximately 6.9 million estimated cases in 2022. The parasite has a dormant liver stage, the hypnozoite, which reactivates to cause repeated relapses over weeks, months, or years. These relapses erode patient health, contribute to the burden of malaria, and promote transmission. Radical cure to prevent relapses requires administration of an 8-aminoquinoline, either primaquine or tafenoquine. However, malaria treatment guidelines updated by the World Health Organization (WHO) in October 2023 restrict primaquine use for women breastfeeding children < 6 months of age, or women breastfeeding older children if their child is G6PD deficient or if the child's G6PD status is unknown. Primaquine restrictions assume that 8-aminoquinoline exposures in breast milk would be sufficient to cause haemolysis in the nursing infant should they be G6PD deficient. WHO recommendations for tafenoquine are awaited. Notably, the WHO recommends that infants are breastfed for the first 2 years of life, and exclusively until 6 months old. Repeated pregnancies, followed by extended breastfeeding leaves women in P. vivax endemic regions potentially vulnerable to relapses for many years. This puts women's health at risk, increases the malaria burden, and perpetuates transmission, hindering malaria control and elimination. The benefits of lifting restrictions on primaquine administration to breastfeeding women are significant, avoiding the adverse consequences of repeated episodes of acute malaria, such as severe anaemia. Recent data challenge the restriction of primaquine in breastfeeding women. Clinical pharmacokinetic data in breastfeeding infants ≥ 28 days old show that the exposure to primaquine is very low and less than 1% of the maternal exposure, indicating negligible risk to infants, irrespective of their G6PD status. Physiologically-based pharmacokinetic modelling complements the clinical data, predicting minimal primaquine exposure to infants and neonates via breast milk from early post-partum. This article summarizes the clinical and modelling evidence for a favourable benefit:risk evaluation of P. vivax radical cure with primaquine for breastfeeding women without the need for infant G6PD testing, supporting a change in policy. This adjustment to current treatment guidelines would support health equity in regard to effective interventions to protect women and their children, enhance malaria control strategies, and advance P. vivax elimination.
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Affiliation(s)
- Nada Abla
- MMV Medicines for Malaria Venture, 20 Route de Pré-Bois, 1215, Geneva 15, Switzerland.
| | - Anne Claire Marrast
- MMV Medicines for Malaria Venture, 20 Route de Pré-Bois, 1215, Geneva 15, Switzerland
| | - Elodie Jambert
- MMV Medicines for Malaria Venture, 20 Route de Pré-Bois, 1215, Geneva 15, Switzerland
| | | | - Stephan Duparc
- MMV Medicines for Malaria Venture, 20 Route de Pré-Bois, 1215, Geneva 15, Switzerland
| | - Lisa Almond
- Certara Predictive Technologies, Simcyp Division, Sheffield, UK
| | | | - Xian Pan
- Certara Predictive Technologies, Simcyp Division, Sheffield, UK
| | - Joel Tarning
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
- Nuffield Department of Clinical Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Ping Zhao
- Bill & Melinda Gates Foundation, Seattle, WA, USA
| | | | - Catriona Waitt
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Charlotte Koldeweij
- Division of Pharmacology Toxicology, Department of Pharmacy, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Susan Cole
- Medicines and Healthcare products Regulatory Agency (MHRA), 10 South Colonnade, London, UK
| | - Andrew S Butler
- Medicines and Healthcare products Regulatory Agency (MHRA), 10 South Colonnade, London, UK
| | - Sonia Khier
- Pharmacokinetic and Modelling Department, School of Pharmacy, IMAG, CNRS, INRIA, UMR 5149, University of Montpellier, Montpellier, France
| | - Jörg J Möhrle
- MMV Medicines for Malaria Venture, 20 Route de Pré-Bois, 1215, Geneva 15, Switzerland
| | - Myriam El Gaaloul
- MMV Medicines for Malaria Venture, 20 Route de Pré-Bois, 1215, Geneva 15, Switzerland
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Abdollahi H, Fele-Paranj A, Rahmim A. Model-Informed Radiopharmaceutical Therapy Optimization: A Study on the Impact of PBPK Model Parameters on Physical, Biological, and Statistical Measures in 177Lu-PSMA Therapy. Cancers (Basel) 2024; 16:3120. [PMID: 39335092 PMCID: PMC11430653 DOI: 10.3390/cancers16183120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2024] [Revised: 09/04/2024] [Accepted: 09/09/2024] [Indexed: 09/30/2024] Open
Abstract
Purpose: To investigate the impact of physiologically based pharmacokinetic (PBPK) parameters on physical, biological, and statistical measures in lutetium-177-labeled radiopharmaceutical therapies (RPTs) targeting the prostate-specific membrane antigen (PSMA). Methods: Using a clinically validated PBPK model, realistic time-activity curves (TACs) for tumors, salivary glands, and kidneys were generated based on various model parameters. These TACs were used to calculate the area-under-the-TAC (AUC), dose, biologically effective dose (BED), and figure-of-merit BED (fBED). The effects of these parameters on radiobiological, pharmacokinetic, time, and statistical features were assessed. Results: Manipulating PBPK parameters significantly influenced AUC, dose, BED, and fBED outcomes across four different BED models. Higher association rates increased AUC, dose, and BED values for tumors, with minimal impact on non-target organs. Increased internalization rates reduced AUC and dose for tumors and kidneys. Higher serum protein-binding rates decreased AUC and dose for all tissues. Elevated tumor receptor density and ligand amounts enhanced uptake and effectiveness in tumors. Larger tumor volumes required dosimetry adjustments to maintain efficacy. Setting the tumor release rate to zero intensified the impact of association and internalization rates, enhancing tumor targeting while minimizing the effects on salivary glands and kidneys. Conclusions: Optimizing PBPK parameters can enhance the efficacy of lutetium-177-labeled RPTs targeting PSMA, providing insights for personalized and effective treatment regimens to minimize toxicity and improve therapeutic outcomes.
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Affiliation(s)
- Hamid Abdollahi
- Department of Radiology, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada;
| | - Ali Fele-Paranj
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada;
- Department of Mathematics, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
| | - Arman Rahmim
- Department of Radiology, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada;
- Department of Physics & Astronomy, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
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12
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Valerie Sia JE, Lai X, Mak WY, Wu X, Zhang F, Cui C, Liu D, Xiang X. Aging-Related CYP3A Functional Changes in Chinese Older Patients: New Findings from Model-Based Assessment of Amlodipine. Clin Pharmacol Ther 2024; 116:858-865. [PMID: 39164849 DOI: 10.1002/cpt.3347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 06/04/2024] [Indexed: 08/22/2024]
Abstract
Aging-related alterations in hepatic enzyme activity, particularly of the CYP3A, significantly impact drug efficacy and safety in older adults, making it essential to understand how aging affects CYP function for optimal drug therapy. The exogenous probe substrate method, a minimally invasive approach to assess liver metabolic enzyme activity in vivo, is effective in studying these changes. Amlodipine being extensively metabolized (> 90%) in the liver, primarily via cytochrome P450 enzyme CYP3A was selected as a probe to investigate and quantify the factors affecting the aging-related changes of CYP3A in the Chinese older population. Amlodipine concentration data were collected from an ongoing noninterventional clinical study conducted at Peking University Third Hospital. A physiologically-based pharmacokinetic modeling approach, grounded in population pharmacokinetic (PPK) analysis, was employed to physiologically quantify the aging-related changes in CYP3A function. A total of 132 amlodipine concentrations from 69 patients were obtained from the clinical study. PPK analysis shows that frailty phenotype but not age is a significant influence and frail patients have 37% greater plasma amlodipine exposure than nonfrail patients. This difference in CYP3A function may be attributed to a 63.2% lower CYP3A relative abundance in the frail patients, compared with that in the nonfrail patients. In the context of dose selection for older adults, focusing on frailty rather than chronological age should be recognized as a more relevant approach, because frailty might more accurately reflect the individual's biological age. Our study suggested a need to shift the research focus from chronological age to biological age.
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Affiliation(s)
- Jie En Valerie Sia
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
- Geriatrics Department, Peking University Third Hospital, Beijing, China
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Xuan Lai
- Geriatrics Department, Peking University Third Hospital, Beijing, China
| | - Wen Yao Mak
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Xinyi Wu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Fan Zhang
- Geriatrics Department, Peking University Third Hospital, Beijing, China
| | - Cheng Cui
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
- Center of Clinical Medical Research, Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
| | - Dongyang Liu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
- Center of Clinical Medical Research, Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Beijing Key Laboratory of Cardiovascular Receptors Research, Peking University Third Hospital, Beijing, China
| | - Xiaoqiang Xiang
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
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13
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Lin J, Bu F, Wu D, Jiang P, He Q, Yang D, Zhu X, Wang Y, Xiang X. Physiologically Based Pharmacokinetic Modeling and Clinical Extrapolation for Topical Application of Pilocarpine on Eyelids: A Comprehensive Study. J Pharm Sci 2024; 113:2861-2870. [PMID: 38857643 DOI: 10.1016/j.xphs.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Revised: 05/31/2024] [Accepted: 06/02/2024] [Indexed: 06/12/2024]
Abstract
Exploiting a convenient and highly bioavailable ocular drug delivery approach is currently one of the hotspots in the pharmaceutical industry. Eyelid topical application is seen to be a valuable strategy in the treatment of chronic ocular diseases. To further elucidate the feasibility of eyelid topical administration as an alternative route for ocular drug delivery, pharmacokinetic and pharmacodynamic studies of pilocarpine were conducted in rabbits. Besides, a novel physiologically based pharmacokinetic (PBPK) model describing eyelid transdermal absorption and ocular disposition was developed in rabbits. The PBPK model of rabbits was extrapolated to human by integrating the drug-specific permeability parameters and human physiological parameters to predict ocular pharmacokinetic in human. After eyelid topical application of pilocarpine, the concentration of pilocarpine in iris peaked at 2 h with the value of 18,724 ng/g and the concentration in aqueous humor peaked at 1 h with the value of 1,363 ng/mL. Significant miotic effect were observed from 0.5 h to 4.5 h after eyelid topical application of pilocarpine in rabbits, while that were observed from 0.5 h to 3.5 h after eyedrop instillation. The proposed eyelid PBPK model was capable of reasonably predicting ocular exposure of pilocarpine after application on the eyelid skin and based on the PBPK model, the human ocular concentration was predicted to be 10-fold lower than that in rabbits. And it was suggested that drugs applied on the eyelid skin could transfer into the eyeball through corneal pathway and scleral pathway. This work could provide pharmacokinetic and pharmacodynamic data for the development of eyelid drug delivery, as well as the reference for clinical applications.
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Affiliation(s)
- Jiaying Lin
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Fengjiao Bu
- Department of Pharmacy, Eye and ENT Hospital, Fudan University, Shanghai 200031, China
| | - Dan Wu
- Department of Facial Plastic and Reconstructive Surgery, Eye and ENT Hospital of Fudan University, Shanghai 200031, China
| | - Pin Jiang
- Shanghai Medicilon Inc., Shanghai 201299, China
| | - Qingfeng He
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Dongsheng Yang
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Xiao Zhu
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China
| | - Yixue Wang
- Pediatric Intensive Care Unit, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China.
| | - Xiaoqiang Xiang
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai 201203, China.
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14
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Li X, Liu S, Liu D, Yu M, Wu X, Wang H. Application of Virtual Drug Study to New Drug Research and Development: Challenges and Opportunity. Clin Pharmacokinet 2024; 63:1239-1249. [PMID: 39225885 DOI: 10.1007/s40262-024-01416-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2024] [Indexed: 09/04/2024]
Abstract
In recent years, virtual drug study, as an emerging research strategy, has become increasingly important in guiding and promoting new drug research and development. Researchers can integrate a variety of technical methods to improve the efficiency of all phases of new drug research and development, including the use of artificial intelligence, modeling and simulation for target identification, compound screening and pharmacokinetic characteristics evaluation, and the application of clinical trial simulation to carry out clinical research. This paper aims to elaborate on the application of virtual drug study in the key stages of new drug research and development and discuss the opportunities and challenges it faces in supporting new drug research and development.
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Affiliation(s)
- Xiuqi Li
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Shupeng Liu
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Dan Liu
- College of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China
| | - Mengyang Yu
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Xiaofei Wu
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Hongyun Wang
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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15
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Jony MR, Ahn S. Drug-Drug Interactions between COVID-19 and Tuberculosis Medications: A Comprehensive Review of CYP450 and Transporter-Mediated Effects. Pharmaceuticals (Basel) 2024; 17:1035. [PMID: 39204140 PMCID: PMC11360778 DOI: 10.3390/ph17081035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 08/02/2024] [Accepted: 08/03/2024] [Indexed: 09/03/2024] Open
Abstract
Most medications undergo metabolism and elimination via CYP450 enzymes, while uptake and efflux transporters play vital roles in drug elimination from various organs. Interactions often occur when multiple drugs share CYP450-transporter-mediated metabolic pathways, necessitating a unique clinical care strategy to address the diverse types of CYP450 and transporter-mediated drug-drug interactions (DDI). The primary focus of this review is to record relevant mechanisms regarding DDI between COVID-19 and tuberculosis (TB) treatments, specifically through the influence of CYP450 enzymes and transporters on drug absorption, distribution, metabolism, elimination, and pharmacokinetics. This understanding empowers clinicians to prevent subtherapeutic and supratherapeutic drug levels of COVID medications when co-administered with TB drugs, thereby mitigating potential challenges and ensuring optimal treatment outcomes. A comprehensive analysis is presented, encompassing various illustrative instances of TB drugs that may impact COVID-19 clinical behavior, and vice versa. This review aims to provide valuable insights to healthcare providers, facilitating informed decision-making and enhancing patient safety while managing co-infections. Ultimately, this study contributes to the body of knowledge necessary to optimize therapeutic approaches and improve patient outcomes in the face of the growing challenges posed by infectious diseases.
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Affiliation(s)
- M. Rasheduzzaman Jony
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Republic of Korea;
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Republic of Korea
| | - Sangzin Ahn
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Republic of Korea;
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Republic of Korea
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16
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Li T, Zhou S, Wang L, Zhao T, Wang J, Shao F. Docetaxel, cyclophosphamide, and epirubicin: application of PBPK modeling to gain new insights for drug-drug interactions. J Pharmacokinet Pharmacodyn 2024; 51:367-384. [PMID: 38554227 DOI: 10.1007/s10928-024-09912-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 02/20/2024] [Indexed: 04/01/2024]
Abstract
The new adjuvant chemotherapy of docetaxel, epirubicin, and cyclophosphamide has been recommended for treating breast cancer. It is necessary to investigate the potential drug-drug Interactions (DDIs) since they have a narrow therapeutic window in which slight differences in exposure might result in significant differences in treatment efficacy and tolerability. To guide clinical rational drug use, this study aimed to evaluate the DDI potentials of docetaxel, cyclophosphamide, and epirubicin in cancer patients using physiologically based pharmacokinetic (PBPK) models. The GastroPlus™ was used to develop the PBPK models, which were refined and validated with observed data. The established PBPK models accurately described the pharmacokinetics (PKs) of three drugs in cancer patients, and the predicted-to-observed ratios of all the PK parameters met the acceptance criterion. The PBPK model predicted no significant changes in plasma concentrations of these drugs during co-administration, which was consistent with the observed clinical phenomenon. Besides, the verified PBPK models were then used to predict the effect of other Cytochrome P450 3A4 (CYP3A4) inhibitors/inducers on these drug exposures. In the DDI simulation, strong CYP3A4 modulators changed the exposure of three drugs by 0.71-1.61 fold. Therefore, patients receiving these drugs in combination with strong CYP3A4 inhibitors should be monitored regularly to prevent adverse reactions. Furthermore, co-administration of docetaxel, cyclophosphamide, or epirubicin with strong CYP3A4 inducers should be avoided. In conclusion, the PBPK models can be used to further investigate the DDI potential of each drug and to develop dosage recommendations for concurrent usage by additional perpetrators or victims.
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Affiliation(s)
- Tongtong Li
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
- Department of Clinical Pharmacology, School of Pharmacy College, Nanjing Medical University, Nanjing, 211166, China
| | - Sufeng Zhou
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
| | - Lu Wang
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
| | - Tangping Zhao
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
- Department of Clinical Pharmacology, School of Pharmacy College, Nanjing Medical University, Nanjing, 211166, China
| | - Jue Wang
- Division of Breast Surgery, The First Affiliated Hospital With Nanjing Medical University, Guangzhou Road 300, Nanjing, 210029, Jiangsu Province, China
| | - Feng Shao
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China.
- Department of Clinical Pharmacology, School of Pharmacy College, Nanjing Medical University, Nanjing, 211166, China.
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17
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Chanteux H, MacPherson M, Kramer H, Otoul C, Okagaki T, Rospo C, De Bruyn S, Watling M, Bani M, Sciberras D. Overview of preclinical and clinical studies investigating pharmacokinetics and drug-drug interactions of padsevonil. Expert Opin Drug Metab Toxicol 2024; 20:841-855. [PMID: 38932723 DOI: 10.1080/17425255.2024.2373108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 06/23/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Padsevonil is an antiseizure medication candidate intended to benefit patients with drug-resistant epilepsy. Our investigations aimed at characterizing pharmacokinetics and drug-drug interaction (DDI) profile of padsevonil. RESEARCH DESIGN AND METHODS An overview of preclinical and clinical pharmacology studies conducted during padsevonil development is provided. RESULTS In preclinical studies, cytochrome (CYP) 3A4 was identified as the main P450 isoform involved in padsevonil metabolism, with potential minor contribution from CYP2C19. Padsevonil was shown to be a time-dependent CYP2C19-inhibitor, weak CYP3A4-inducer, weak inhibitor of P-gp/OCT1/MATE2-K, and potent OCT2-inhibitor. Initial clinical pharmacology studies in healthy participants showed that padsevonil had (i) good absorption, (ii) clearance mediated mainly by metabolism, and (iii) time-dependent kinetics. A study in genotyped participants confirmed the role of CYP2C19 in clearance and time-dependent kinetics; the major contribution of CYP3A4 was confirmed in DDI studies with CYP3A4-inducers (carbamazepine, oxcarbazepine) and -inhibitor (erythromycin). Padsevonil did not affect pharmacokinetics of valproate/lamotrigine/levetiracetam/oxcarbazepine or oral contraceptives. In a cocktail clinical study, padsevonil showed moderate CYP2C19 inhibition (omeprazole) and weak CYP3A4 induction (oral midazolam). No specific effects on CYP1A2 (caffeine), CYP2C9 (S-warfarin), and CYP2D6 (dextromethorphan) were observed. CONCLUSIONS The studies presented helped in understanding padsevonil disposition and risks of DDIs, which would inform dosing and prescribing. CLINICAL TRIAL REGISTRATION https://www.clinicaltrials.gov identifiers are NCT04131517, NCT03480243, NCT03695094, NCT04075409.
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18
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Wu YE, Zheng YY, Li QY, Yao BF, Cao J, Liu HX, Hao GX, van den Anker J, Zheng Y, Zhao W. Model-informed drug development in pediatric, pregnancy and geriatric drug development: States of the art and future. Adv Drug Deliv Rev 2024; 211:115364. [PMID: 38936664 DOI: 10.1016/j.addr.2024.115364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 06/09/2024] [Accepted: 06/19/2024] [Indexed: 06/29/2024]
Abstract
The challenges of drug development in pediatric, pregnant and geriatric populations are a worldwide concern shared by regulatory authorities, pharmaceutical companies, and healthcare professionals. Model-informed drug development (MIDD) can integrate and quantify real-world data of physiology, pharmacology, and disease processes by using modeling and simulation techniques to facilitate decision-making in drug development. In this article, we reviewed current MIDD policy updates, reflected on the integrity of physiological data used for MIDD and the effects of physiological changes on the drug PK, as well as summarized current MIDD strategies and applications, so as to present the state of the art of MIDD in pediatric, pregnant and geriatric populations. Some considerations are put forth for the future improvements of MIDD including refining regulatory considerations, improving the integrity of physiological data, applying the emerging technologies, and exploring the application of MIDD in new therapies like gene therapies for special populations.
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Affiliation(s)
- Yue-E Wu
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yuan-Yuan Zheng
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Qiu-Yue Li
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Bu-Fan Yao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Jing Cao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Hui-Xin Liu
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Guo-Xiang Hao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - John van den Anker
- Division of Clinical Pharmacology, Children's National Medical Center, Washington, DC, USA; Departments of Pediatrics, Pharmacology & Physiology, George Washington University, School of Medicine and Health Sciences, Washington, DC, USA; Department of Paediatric Pharmacology and Pharmacometrics, University Children's Hospital Basel, Basel, Switzerland
| | - Yi Zheng
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wei Zhao
- Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
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19
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Geci R, Gadaleta D, de Lomana MG, Ortega-Vallbona R, Colombo E, Serrano-Candelas E, Paini A, Kuepfer L, Schaller S. Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans. Arch Toxicol 2024; 98:2659-2676. [PMID: 38722347 PMCID: PMC11272695 DOI: 10.1007/s00204-024-03764-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 04/23/2024] [Indexed: 07/26/2024]
Abstract
Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for non-animal methods. To address this limitation, high-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000 + publicly available human in vivo concentration-time profiles of 200 + compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration-time profiles. Our results show that even simple, generic high-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within tenfold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for high-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of high-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.
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Affiliation(s)
- René Geci
- esqLABS GmbH, Saterland, Germany.
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany.
| | | | - Marina García de Lomana
- Machine Learning Research, Research and Development, Pharmaceuticals, Bayer AG, Berlin, Germany
| | | | - Erika Colombo
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | | | | | - Lars Kuepfer
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
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Arav Y. Advances in Modeling Approaches for Oral Drug Delivery: Artificial Intelligence, Physiologically-Based Pharmacokinetics, and First-Principles Models. Pharmaceutics 2024; 16:978. [PMID: 39204323 PMCID: PMC11359797 DOI: 10.3390/pharmaceutics16080978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/17/2024] [Accepted: 07/22/2024] [Indexed: 09/04/2024] Open
Abstract
Oral drug absorption is the primary route for drug administration. However, this process hinges on multiple factors, including the drug's physicochemical properties, formulation characteristics, and gastrointestinal physiology. Given its intricacy and the exorbitant costs associated with experimentation, the trial-and-error method proves prohibitively expensive. Theoretical models have emerged as a cost-effective alternative by assimilating data from diverse experiments and theoretical considerations. These models fall into three categories: (i) data-driven models, encompassing classical pharmacokinetics, quantitative-structure models (QSAR), and machine/deep learning; (ii) mechanism-based models, which include quasi-equilibrium, steady-state, and physiologically-based pharmacokinetics models; and (iii) first principles models, including molecular dynamics and continuum models. This review provides an overview of recent modeling endeavors across these categories while evaluating their respective advantages and limitations. Additionally, a primer on partial differential equations and their numerical solutions is included in the appendix, recognizing their utility in modeling physiological systems despite their mathematical complexity limiting widespread application in this field.
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Affiliation(s)
- Yehuda Arav
- Department of Applied Mathematics, Israeli Institute for Biological Research, P.O. Box 19, Ness-Ziona 7410001, Israel
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21
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Koldeweij C, Kleuskens M, Litjens C, Franklin BD, Scheepers HCJ, de Wildt SN. Perceived barriers and facilitators for model-informed dosing in pregnancy: a qualitative study across healthcare practitioners and pregnant women. BMC Med 2024; 22:248. [PMID: 38886762 PMCID: PMC11184760 DOI: 10.1186/s12916-024-03450-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 05/28/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Most women use medication during pregnancy. Pregnancy-induced changes in physiology may require antenatal dose alterations. Yet, evidence-based doses in pregnancy are missing. Given historically limited data, pharmacokinetic models may inform pregnancy-adjusted doses. However, implementing model-informed doses in clinical practice requires support from relevant stakeholders. PURPOSE To explore the perceived barriers and facilitators for model-informed antenatal doses among healthcare practitioners (HCPs) and pregnant women. METHODS Online focus groups and interviews were held among healthcare practitioners (HCPs) and pregnant women from eight countries across Europe, Africa and Asia. Purposive sampling was used to identify pregnant women plus HCPs across various specialties prescribing or providing advice on medication to pregnant women. Perceived barriers and facilitators for implementing model-informed doses in pregnancy were identified and categorised using a hybrid thematic analysis. RESULTS Fifty HCPs and 11 pregnant women participated in 12 focus groups and 16 interviews between January 2022 and March 2023. HCPs worked in the Netherlands (n = 32), the UK (n = 7), South Africa (n = 5), Uganda (n = 4), Kenya, Cameroon, India and Vietnam (n = 1 each). All pregnant women resided in the Netherlands. Barriers and facilitators identified by HCPs spanned 14 categories across four domains whereas pregnant women described barriers and facilitators spanning nine categories within the same domains. Most participants found current antenatal dosing information inadequate and regarded model-informed doses in pregnancy as a valuable and for some, much-needed addition to antenatal care. Although willingness-to-follow model-informed antenatal doses was high across both groups, several barriers for implementation were identified. HCPs underlined the need for transparent model validation and endorsement of the methodology by recognised institutions. Foetal safety was deemed a critical knowledge gap by both groups. HCPs' information needs and preferred features for model-informed doses in pregnancy varied. Several pregnant women expressed a desire to access information and partake in decisions on antenatal dosing. CONCLUSIONS Given the perceived limitations of current pharmacotherapy for pregnant women and foetuses, model-informed dosing in pregnancy was seen as a promising means to enhance antenatal care by pregnant women and healthcare practitioners.
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Affiliation(s)
- Charlotte Koldeweij
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Mirèse Kleuskens
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Carlijn Litjens
- Netherlands Pharmacovigilance Centre Lareb, 's-Hertogenbosch, The Netherlands
| | - Bryony Dean Franklin
- Centre for Medication Safety and Service Quality, Imperial College Healthcare NHS Trust, London, UK
- Department of Practice and Policy, UCL School of Pharmacy, London, UK
| | - Hubertina C J Scheepers
- Department of Obstetrics and Gynaecology, Maastricht University Medical Centre, Maastricht, The Netherlands
- Grow, School for Oncology and Reproduction, Maastricht, The Netherlands
| | - Saskia N de Wildt
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Pediatric and Neonatal Intensive Care, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
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22
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Wang M, Heimbach T, Zhu W, Wu D, Reuter KG, Kesisoglou F. Physiologically Based Biopharmaceutics Modeling for Gefapixant IR Formulation Development and Defining the Bioequivalence Dissolution Safe Space. AAPS J 2024; 26:69. [PMID: 38862807 DOI: 10.1208/s12248-024-00938-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 05/29/2024] [Indexed: 06/13/2024] Open
Abstract
Gefapixant is a weakly basic drug which has been formulated as an immediate release tablet for oral administration. A physiologically based biopharmaceutics model (PBBM) was developed based on gefapixant physicochemical properties and clinical pharmacokinetics to aid formulation selection, bioequivalence safe space assessment and dissolution specification settings. In vitro dissolution profiles of different free base and citrate salt formulations were used as an input to the model. The model was validated against the results of independent studies, which included a bioequivalence and a relative bioavailability study, as well as a human ADME study, all meeting acceptance criteria of prediction errors ≤ 20% for both Cmax and AUC. PBBM was also applied to evaluate gastric pH-mediated drug-drug-interaction potential with co-administration of a proton pump inhibitor (PPI), omeprazole. Model results showed good agreement with clinical data in which omeprazole lowered gefapixant exposure for the free base formulation but did not significantly alter gefapixant pharmacokinetics for the citrate based commercial drug product. An extended virtual dissolution bioequivalence safe space was established. Gefapixant drug product batches are anticipated to be bioequivalent with the clinical reference batch when their dissolution is > 80% in 60 minutes. PBBM established a wide dissolution bioequivalence space as part of assuring product quality.
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Affiliation(s)
- Michael Wang
- Pharmaceutical Sciences, MRL, Merck & Co., Inc, Rahway, NJ, 07065, USA
| | - Tycho Heimbach
- Pharmaceutical Sciences, MRL, Merck & Co., Inc, Rahway, NJ, 07065, USA.
| | - Wei Zhu
- Clinical Pharmacology and Pharmacometrics, Janssen Research & Development, Raritan, NJ, USA
| | - Di Wu
- Pharmaceutical Sciences, MRL, Merck & Co., Inc, Rahway, NJ, 07065, USA
| | - Kevin G Reuter
- Pharmaceutical Sciences, MRL, Merck & Co., Inc, Rahway, NJ, 07065, USA
- Analytical Sciences, Haleon, 1211 Sherwood Ave., Richmond, VA, 23220, USA
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Achan J, Barry A, Leroy D, Kamara G, Duparc S, Kaszubska W, Gandhi P, Buffet B, Tshilab P, Ogutu B, Taylor T, Krishna S, Richardson N, Ramachandruni H, Rietveld H. Defining the next generation of severe malaria treatment: a target product profile. Malar J 2024; 23:174. [PMID: 38835069 DOI: 10.1186/s12936-024-04986-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 05/14/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Severe malaria is a life-threatening infection, particularly affecting children under the age of 5 years in Africa. Current treatment with parenteral artemisinin derivatives is highly efficacious. However, artemisinin partial resistance is widespread in Southeast Asia, resulting in delayed parasite clearance after therapy, and has emerged independently in South America, Oceania, and Africa. Hence, new treatments for severe malaria are needed, and it is prudent to define their characteristics now. This manuscript focuses on the target product profile (TPP) for new treatments for severe malaria. It also highlights preparedness when considering ways of protecting the utility of artemisinin-based therapies. TARGET PRODUCT PROFILE Severe malaria treatments must be highly potent, with rapid onset of antiparasitic activity to clear the infection as quickly as possible to prevent complications. They should also have a low potential for drug resistance selection, given the high parasite burden in patients with severe malaria. Combination therapies are needed to deter resistance selection and dissemination. Partner drugs which are approved for uncomplicated malaria treatment would provide the most rapid development pathway for combinations, though new candidate molecules should be considered. Artemisinin combination approaches to severe malaria would extend the lifespan of current therapy, but ideally, completely novel, non-artemisinin-based combination therapies for severe malaria should be developed. These should be advanced to at least phase 2 clinical trials, enabling rapid progression to patient use should current treatment fail clinically. New drug combinations for severe malaria should be available as injectable formulations for rapid and effective treatment, or as rectal formulations for pre-referral intervention in resource-limited settings. CONCLUSION Defining the TPP is a key step to align responses across the community to proactively address the potential for clinical failure of artesunate in severe malaria. In the shorter term, artemisinin-based combination therapies should be developed using approved or novel drugs. In the longer term, novel combination treatments should be pursued. Thus, this TPP aims to direct efforts to preserve the efficacy of existing treatments while improving care and outcomes for individuals affected by this life-threatening disease.
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Affiliation(s)
| | - Aïssata Barry
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Didier Leroy
- Medicines for Malaria Venture, Route de Pré-Bois 20, Post Box 1826, CH-1215, Geneva 15, Switzerland
| | - George Kamara
- Médecins Sans Frontières, Magburaka District Hospital, Freetown, Sierra Leone
| | - Stephan Duparc
- Medicines for Malaria Venture, Route de Pré-Bois 20, Post Box 1826, CH-1215, Geneva 15, Switzerland
| | - Wiweka Kaszubska
- Medicines for Malaria Venture, Route de Pré-Bois 20, Post Box 1826, CH-1215, Geneva 15, Switzerland
| | | | - Bénédicte Buffet
- Medicines for Malaria Venture, Route de Pré-Bois 20, Post Box 1826, CH-1215, Geneva 15, Switzerland
| | | | - Bernhards Ogutu
- Centre for Clinical Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Terrie Taylor
- Queen Elizabeth Central Hospital and Blantyre Malaria Project, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Sanjeev Krishna
- Institut Für Tropenmedizin, Eberhard Karls Universität Tübingen, and German Center for Infection Research (Dzif), Tübingen, Germany
- Centre de Recherches Médicales de Lambaréné (CERMEL), Lambaréné, Gabon
- Clinical Academic Group, Institute for Infection and Immunity, St. George's University of London, London, UK
- St George's University Hospitals NHS Foundation Trust, London, UK
| | | | - Hanu Ramachandruni
- Medicines for Malaria Venture, Route de Pré-Bois 20, Post Box 1826, CH-1215, Geneva 15, Switzerland.
| | - Hans Rietveld
- Medicines for Malaria Venture, Route de Pré-Bois 20, Post Box 1826, CH-1215, Geneva 15, Switzerland.
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24
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Bassani D, Parrott NJ, Manevski N, Zhang JD. Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules. Expert Opin Drug Discov 2024; 19:683-698. [PMID: 38727016 DOI: 10.1080/17460441.2024.2348157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 04/23/2024] [Indexed: 05/22/2024]
Abstract
INTRODUCTION Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structures) and target variables (such as PK parameters), are being increasingly used for this purpose. To embed ML models for PK prediction into workflows and to guide future development, a solid understanding of their applicability, advantages, limitations, and synergies with other approaches is necessary. AREAS COVERED This narrative review discusses the design and application of ML models to predict PK parameters of small molecules, especially in light of established approaches including in vitro-in vivo extrapolation (IVIVE) and physiologically based pharmacokinetic (PBPK) models. The authors illustrate scenarios in which the three approaches are used and emphasize how they enhance and complement each other. In particular, they highlight achievements, the state of the art and potentials of applying machine learning for PK prediction through a comphrehensive literature review. EXPERT OPINION ML models, when carefully crafted, regularly updated, and appropriately used, empower users to prioritize molecules with favorable PK properties. Informed practitioners can leverage these models to improve the efficiency of drug discovery and development process.
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Affiliation(s)
- Davide Bassani
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Neil John Parrott
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Nenad Manevski
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Jitao David Zhang
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
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25
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Ni L, Cao Z, Jiang J, Zhang W, Hu W, Zhang Q, Shen C, Chen X, Zheng L. Evaluating Drug Interactions between Ritonavir and Opioid Analgesics: Implications from Physiologically Based Pharmacokinetic Simulation. Pharmaceuticals (Basel) 2024; 17:640. [PMID: 38794210 PMCID: PMC11124264 DOI: 10.3390/ph17050640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/05/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Several commonly used opioid analgesics, such as fentanyl, sufentanil, alfentanil, and hydrocodone, are by report primarily metabolized by the CYP3A4 enzyme. The concurrent use of ritonavir, a potent CYP3A4 inhibitor, can lead to significant drug interactions. Using physiologically based pharmacokinetic (PBPK) modeling and simulation, this study examines the effects of different dosing regimens of ritonavir on the pharmacokinetics of these opioids. The findings reveal that co-administration of ritonavir significantly increases the exposure of fentanyl analogs, with over a 10-fold increase in the exposure of alfentanil and sufentanil when given with ritonavir. Conversely, the effect of ritonavir on fentanyl exposure is modest, likely due to additional metabolism pathways. Additionally, the study demonstrates that the steady-state exposure of hydrocodone and its active metabolite hydromorphone can be increased by up to 87% and 95%, respectively, with concurrent use of ritonavir. The extended-release formulation of hydrocodone is particularly affected. These insights from PBPK modeling provide valuable guidance for optimizing opioid dosing and minimizing the risk of toxicity when used in combination with ritonavir-containing prescriptions.
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Affiliation(s)
- Liang Ni
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, China;
| | - Zhihai Cao
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (Z.C.); (W.Z.); (W.H.); (Q.Z.)
- School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Jiakang Jiang
- Department of Pharmacy and Biomedical Engineering, Clinical College of Anhui Medical University, Hefei 230031, China;
| | - Wei Zhang
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (Z.C.); (W.Z.); (W.H.); (Q.Z.)
| | - Wei Hu
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (Z.C.); (W.Z.); (W.H.); (Q.Z.)
| | - Qian Zhang
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (Z.C.); (W.Z.); (W.H.); (Q.Z.)
| | - Chaozhuang Shen
- Department of Clinical Pharmacy and Pharmacy Administration, West China School of Pharmacy, Sichuan University, Chengdu 610041, China;
| | - Xijing Chen
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, China;
| | - Liang Zheng
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (Z.C.); (W.Z.); (W.H.); (Q.Z.)
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26
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Wu D, Liu J, Paragas EM, Yadav J, Aliwarga T, Heimbach T, Escotet-Espinoza MS. Assessing and mitigating pH-mediated DDI risks in drug development - formulation approaches and clinical considerations. Drug Metab Rev 2024:1-20. [PMID: 38700278 DOI: 10.1080/03602532.2024.2345632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/10/2024] [Indexed: 05/05/2024]
Abstract
pH-mediated drug-drug interactions (DDI) is a prevalent DDI in drug development, especially for weak base compounds with highly pH-dependent solubility. FDA has released a guidance on the evaluation of pH-mediated DDI assessments using in vitro testing and clinical studies. Currently, there is no common practice of ways of testing across the academia and industry. The development of biopredictive method and physiologically-based biopharmaceutics modeling (PBBM) approaches to assess acid-reducing agent (ARA)-DDI have been proven with accurate prediction and could decrease drug development burden, inform clinical design and potentially waive clinical studies. Formulation strategies and careful clinical design could help mitigate the pH-mediated DDI to avoid more clinical studies and label restrictions, ultimately benefiting the patient. In this review paper, a detailed introduction on biorelevant dissolution testing, preclinical and clinical study requirement and PBPK modeling approaches to assess ARA-DDI are described. An improved decision tree for pH-mediated DDI is proposed. Potential mitigations including clinical or formulation strategies are discussed.
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Affiliation(s)
- Di Wu
- Pharmaceutical Sciences & Clinical Supply, Merck & Co., Inc, Rahway, NJ, USA
| | - Jiaying Liu
- Pharmaceutical Sciences & Clinical Supply, Merck & Co., Inc, Rahway, NJ, USA
| | - Erickson M Paragas
- Pharmacokinetics and Drug Metabolism Department, Amgen Research, South San Francisco, CA, USA
| | - Jaydeep Yadav
- Pharmacokinetics, Pharmacodynamics, and Drug Metabolism, Merck & Co., Inc, Boston, MA, USA
| | - Theresa Aliwarga
- Pharmacokinetics and Drug Metabolism Department, Amgen Research, South San Francisco, CA, USA
| | - Tycho Heimbach
- Pharmaceutical Sciences & Clinical Supply, Merck & Co., Inc, Rahway, NJ, USA
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27
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Kesharwani SS, Louit G, Ibrahim F. The Use of Global Sensitivity Analysis to Assess the Oral Absorption of Weakly Basic Compounds: A Case Example of Dipyridamole. Pharm Res 2024; 41:877-890. [PMID: 38538971 DOI: 10.1007/s11095-024-03688-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 03/04/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVE To utilize the global system analysis (GSA) in oral absorption modeling to gain a deeper understanding of system behavior, improve model accuracy, and make informed decisions during drug development. METHODS GSA was utilized to give insight into which drug substance (DS), drug product (DP), and/or physiological parameter would have an impact on peak plasma concentration (Cmax) and area under the curve (AUC) of dipyridamole as a model weakly basic compound. GSA guided the design of in vitro experiments and oral absorption risk assessment using FormulatedProducts v2202.1.0. The solubility and precipitation profiles of dipyridamole in different bile salt concentrations were measured. The results were then used to build a mechanistic oral absorption model. RESULTS GSA warranted further investigation into the precipitation kinetics and its link to the levels of bile salt concentrations. Mechanistic modeling studies demonstrated that a precipitation-integrated modeling approach appropriately predicted the mean plasma profiles, Cmax, and AUC from the clinical studies. CONCLUSIONS This work shows the value of GSA utilization in early development to guide in vitro experimentation and build more confidence in identifying the critical parameters for the mathematical models.
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Affiliation(s)
- Siddharth S Kesharwani
- US Early Development Biopharmacy, Synthetics Platform, Sanofi, 350 Water St, Cambridge, MA, 02141, USA
| | - Guillaume Louit
- Siemens K.K, DI SW Division, 1-6-1 Miyahara, Osaka, 532-0003, Japan
| | - Fady Ibrahim
- US Early Development Biopharmacy, Synthetics Platform, Sanofi, 350 Water St, Cambridge, MA, 02141, USA.
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28
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Allegaert K, Quinney SK, Dallmann A. Physiologically Based Pharmacokinetic Modeling in Pregnancy, during Lactation and in Neonates: Achievements, Challenges and Future Directions. Pharmaceutics 2024; 16:500. [PMID: 38675161 PMCID: PMC11053422 DOI: 10.3390/pharmaceutics16040500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024] Open
Abstract
Obstetric subjects represent a special population in pharmacology [...].
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Affiliation(s)
- Karel Allegaert
- Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
- Department of Hospital Pharmacy, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Sara K. Quinney
- Department of OB/GYN, Maternal and Pediatric Precision in Therapeutics (MPRINT) Hub, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - André Dallmann
- Bayer HealthCare SAS, Loos, France, on Behalf of Bayer AG, Pharmacometrics/Modeling and Simulation, Systems Pharmacology & Medicine–PBPK, 51368 Leverkusen, Germany;
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29
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Hsu JC, Wu M, Kim C, Vora B, Lien YTK, Jindal A, Yoshida K, Kawakatsu S, Gore J, Jin JY, Lu C, Chen B, Wu B. Applications of Advanced Natural Language Processing for Clinical Pharmacology. Clin Pharmacol Ther 2024; 115:786-794. [PMID: 38140747 DOI: 10.1002/cpt.3161] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/20/2023] [Indexed: 12/24/2023]
Abstract
Natural language processing (NLP) is a branch of artificial intelligence, which combines computational linguistics, machine learning, and deep learning models to process human language. Although there is a surge in NLP usage across various industries in recent years, NLP has not been widely evaluated and utilized to support drug development. To demonstrate how advanced NLP can expedite the extraction and analyses of information to help address clinical pharmacology questions, inform clinical trial designs, and support drug development, three use cases are described in this article: (1) dose optimization strategy in oncology, (2) common covariates on pharmacokinetic (PK) parameters in oncology, and (3) physiologically-based PK (PBPK) analyses for regulatory review and product label. The NLP workflow includes (1) preparation of source files, (2) NLP model building, and (3) automation of data extraction. The Clinical Pharmacology and Biopharmaceutics Summary Basis of Approval (SBA) documents, US package inserts (USPI), and approval letters from the US Food and Drug Administration (FDA) were used as our source data. As demonstrated in the three example use cases, advanced NLP can expedite the extraction and analyses of large amounts of information from regulatory review documents to help address important clinical pharmacology questions. Although this has not been adopted widely, integrating advanced NLP into the clinical pharmacology workflow can increase efficiency in extracting impactful information to advance drug development.
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Affiliation(s)
- Joy C Hsu
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
| | - Michael Wu
- Computational Sciences, Genentech, Inc., South San Francisco, California, USA
| | - Chloe Kim
- Computational Sciences, Genentech, Inc., South San Francisco, California, USA
| | - Bianca Vora
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
| | - Yi Ting Kayla Lien
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
| | - Ashutosh Jindal
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
| | - Kenta Yoshida
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
| | - Sonoko Kawakatsu
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
- A2-Ai, Ann Arbor, Michigan, USA
| | - Jeremy Gore
- Capgemini America, Inc., New York, New York, USA
| | - Jin Y Jin
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
| | - Christina Lu
- Computational Sciences, Genentech, Inc., South San Francisco, California, USA
| | - Bingyuan Chen
- Computational Sciences, Genentech, Inc., South San Francisco, California, USA
| | - Benjamin Wu
- Clinical Pharmacology, Genentech, Inc., South San Francisco, California, USA
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30
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Wang X, Wu J, Ye H, Zhao X, Zhu S. Research Landscape of Physiologically Based Pharmacokinetic Model Utilization in Different Fields: A Bibliometric Analysis (1999-2023). Pharm Res 2024; 41:609-622. [PMID: 38383936 DOI: 10.1007/s11095-024-03676-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/05/2024] [Indexed: 02/23/2024]
Abstract
PURPOSE The physiologically based pharmacokinetic (PBPK) modeling has received increasing attention owing to its excellent predictive abilities. However, there has been no bibliometric analysis about PBPK modeling. This research aimed to summarize the research development and hot points in PBPK model utilization overall through bibliometric analysis. METHODS We searched for publications related to the PBPK modeling from 1999 to 2023 in the Web of Science Core Collection (WoSCC) database. The Microsoft Office Excel, CiteSpace and VOSviewers were used to perform the analyses. RESULTS A total of 4,649 records from 1999 to 2023 were identified, and the largest number of publications focused in the period 2018-2023. The United States was the leading country, and the Environmental Protection Agency (EPA) was the leading institution. The journal Drug Metabolism and Disposition published and co-cited the most articles. Drug-drug interactions, special populations, and new drug development are the main topics in this research field. CONCLUSION We first visualize the research landscape and hotspots of the PBPK modeling through bibliometric methods. Our study provides a better understanding for researchers, especially beginners about the dynamization of PBPK modeling and presents the relevant trend in the future.
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Affiliation(s)
- Xin Wang
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Jiangfan Wu
- School of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Hongjiang Ye
- Department of Neurosurgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaofang Zhao
- School of Pharmacy, Chongqing Medical University, Chongqing, China
- Qiandongnan Miao and Dong Autonomous Prefecture People's Hospital, Guizhou, 556000, China
| | - Shenyin Zhu
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing, 400016, China.
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31
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Wang R, Wang T, Han X, Chen M, Li S. Development of a physiologically based pharmacokinetic model for levetiracetam in patients with renal impairment to guide dose adjustment based on steady-state peak/trough concentrations. Xenobiotica 2024; 54:116-123. [PMID: 38344757 DOI: 10.1080/00498254.2024.2317888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/08/2024] [Indexed: 02/22/2024]
Abstract
Levetiracetam may cause acute renal failure and myoclonic encephalopathy at high plasma levels, particularly in patients with renal impairment. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict levetiracetam pharmacokinetics in Chinese adults with epilepsy and renal impairment and define appropriate levetiracetam dosing regimen.PBPK models for healthy subjects and epilepsy patients with renal impairment were developed, validated, and adapted. Furthermore, we predicted the steady-state trough and peak concentrations of levetiracetam in patients with renal impairment using the final PBPK model, thereby recommending appropriate levetiracetam dosing regimens for different renal function stages. The predicted maximum plasma concentration (Cmax), time to maximum concentration (Tmax), area under the plasma concentration-time curve (AUC) were in agreement (0.8 ≤ fold error ≤ 1.2) with the observed, and the fold error of the trough concentrations in end-stage renal disease (ESRD) was 0.77 - 1.22. The prediction simulations indicated that the recommended doses of 1000, 750, 500, and 500 mg twice daily for epilepsy patients with mild, moderate, severe renal impairment, and ESRD, respectively, were sufficient to achieve the target plasma concentration of levetiracetam.
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Affiliation(s)
- Rongrong Wang
- Department of Pharmacy, Medical Security Center, Chinese PLA General Hospital, Beijing, People's Republic of China
| | - Tianlin Wang
- Department of Pharmacy, Medical Security Center, Chinese PLA General Hospital, Beijing, People's Republic of China
| | - Xueliang Han
- Chinese PAP qinghai Hospital, Xining, People's Republic of China
| | - Mengli Chen
- Department of Pharmacy, Medical Security Center, Chinese PLA General Hospital, Beijing, People's Republic of China
| | - Shu Li
- Department of Pharmacy, Medical Security Center, Chinese PLA General Hospital, Beijing, People's Republic of China
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Zheng L, Zhang W, Olkkola KT, Dallmann A, Ni L, Zhao Y, Wang L, Zhang Q, Hu W. Physiologically based pharmacokinetic modeling of ritonavir-oxycodone drug interactions and its implication for dosing strategy. Eur J Pharm Sci 2024; 194:106697. [PMID: 38199444 DOI: 10.1016/j.ejps.2024.106697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/13/2023] [Accepted: 01/07/2024] [Indexed: 01/12/2024]
Abstract
The concomitant administration of ritonavir and oxycodone may significantly increase the plasma concentrations of oxycodone. This study was aimed to simulate DDI between ritonavir and oxycodone, a widely used opioid, and to formulate dosing protocols for oxycodone by using physiologically based pharmacokinetic (PBPK) modeling. We developed a ritonavir PBPK model incorporating induction and competitive and time-dependent inhibition of CYP3A4 and competitive inhibition of CYP2D6. The ritonavir model was evaluated with observed clinical pharmacokinetic data and validated for its CYP3A4 inhibition potency. We then used the model to simulate drug interactions between oxycodone and ritonavir under various dosing scenarios. The developed model captured the pharmacokinetic characteristics of ritonavir from clinical studies. The model also accurately predicts exposure changes of midazolam, triazolam, and oxycodone in the presence of ritonavir. According to model simulations, the steady-state maximum, minimum and average concentrations of oxycodone increased by up to 166% after co-administration with ritonavir, and the total exposure increased by approximately 120%. To achieve similar steady-state concentrations, halving the dose with an unchanged dosing interval or doubling the dosing interval with an unaltered single dose should be practical for oxycodone, whether formulated in uncoated or controlled-release tablets during long-term co-medication with ritonavir. The results revealed exposure-related risks of oxycodone-ritonavir interactions that have not been studied clinically and emphasized PBPK as a workable method to direct judicious dosage.
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Affiliation(s)
- Liang Zheng
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
| | - Wei Zhang
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Klaus T Olkkola
- Department of Anaesthesiology and Intensive Care Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
| | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany.
| | - Liang Ni
- Clinical Pharmacokinetics Laboratory, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Yingjie Zhao
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ling Wang
- Department of Clinical Pharmacy and Pharmacy Administration, West China School of Pharmacy, Sichuan University, Chengdu, China
| | - Qian Zhang
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
| | - Wei Hu
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
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Pan J, Cai Y, He H, Gu N, Li Z. A multiscale modeling study of nanoparticle-based targeting therapy against atherosclerosis. J Biomech 2024; 166:112067. [PMID: 38556387 DOI: 10.1016/j.jbiomech.2024.112067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 03/19/2024] [Accepted: 03/25/2024] [Indexed: 04/02/2024]
Abstract
Although researches on nanoparticle-based (NP-based) drug delivery system for atherosclerosis treatment have grown rapidly in recent years, there are limited studies in quantifying the effects of targeting drugs on plaque components and microenvironment. The purpose of the present study was to quantitatively assess the targeting therapeutic effects against atherosclerosis by establishing a multiscale mathematical model. The multiscale model involved subcellular, cellular and microenvironmental scales to simulate lipid catabolism, macrophage behaviors and dynamics of microenvironmental components, respectively. In vitro and in vivo experimental data were integrated into the mathematical model according to Bayesian statistics, in order to evaluate the therapeutic effects of a proposed NP-based platform for macrophage-specific delivery to simultaneously deliver SR-A siRNA (to reduce LDL uptake) and LXR-L (to stimulate cholesterol efflux). Dosage variation analysis was then performed to investigate the drug efficacy under varied dosage combinations of SR-A siRNA and LXR-L. The simulation results demonstrated that the dynamics of the microenvironmental components presented different developments in Untreated and Treated groups. We also found that the balance of lipid metabolism between uptake and efflux resulted in the improvement of lipid and inflammatory microenvironment, consequently in the plaque regression. In addition, the model predicted optimized dosage combinations according to the co-effect analysis of the two drugs on the lipid microenvironment. This study suggests that multiscale modeling can be a powerful quantitative tool for estimating the therapeutic effects of targeting drugs for plaque regression and designing the enhanced treatment strategies against atherosclerosis.
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Affiliation(s)
- Jichao Pan
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Yan Cai
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Hongliang He
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China.
| | - Ning Gu
- Nanjing Key Laboratory for Cardiovascular Information and Health Engineering Medicine, Institute of Clinical Medicine, Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing 210093, China.
| | - Zhiyong Li
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China; School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4001, Australia; Faculty of Sports Science, Ningbo University, Ningbo 315211, China.
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Marques L, Costa B, Pereira M, Silva A, Santos J, Saldanha L, Silva I, Magalhães P, Schmidt S, Vale N. Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare. Pharmaceutics 2024; 16:332. [PMID: 38543226 PMCID: PMC10975777 DOI: 10.3390/pharmaceutics16030332] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 02/21/2024] [Accepted: 02/25/2024] [Indexed: 11/12/2024] Open
Abstract
The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient's uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the "five rights": the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug-drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come.
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Affiliation(s)
- Lara Marques
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Bárbara Costa
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Mariana Pereira
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- ICBAS—School of Medicine and Biomedical Sciences, University of Porto, Rua de Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
| | - Abigail Silva
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Biomedicine, Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Joana Santos
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Leonor Saldanha
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Isabel Silva
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
| | - Paulo Magalhães
- Coimbra Institute for Biomedical Imaging and Translational Research, Edifício do ICNAS, Polo 3 Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal;
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, 6550 Sanger Road, Office 465, Orlando, FL 328227-7400, USA;
| | - Nuno Vale
- PerMed Research Group, Center for Health Technology and Services Research (CINTESIS), Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal; (L.M.); (B.C.); (M.P.); (A.S.); (J.S.); (L.S.); (I.S.)
- CINTESIS@RISE, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal
- Department of Community Medicine, Health Information and Decision (MEDCIDS), Faculty of Medicine, University of Porto, Rua Doutor Plácido da Costa, 4200-450 Porto, Portugal
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Lee JM, Yoon JH, Maeng HJ, Kim YC. Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict CYP3A-Mediated Drug Interaction between Saxagliptin and Nicardipine: Bridging Rat-to-Human Extrapolation. Pharmaceutics 2024; 16:280. [PMID: 38399334 PMCID: PMC10892660 DOI: 10.3390/pharmaceutics16020280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 02/09/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
The aim of this study was to predict the cytochrome P450 3A (CYP3A)-mediated drug-drug interactions (DDIs) between saxagliptin and nicardipine using a physiologically based pharmacokinetic (PBPK) model. Initially, in silico and in vitro parameters were gathered from experiments or the literature to construct PBPK models for each drug in rats. These models were integrated to predict the DDIs between saxagliptin, metabolized via CYP3A2, and nicardipine, exhibiting CYP3A inhibitory activity. The rat DDI PBPK model was completed by optimizing parameters using experimental rat plasma concentrations after co-administration of both drugs. Following co-administration in Sprague-Dawley rats, saxagliptin plasma concentration significantly increased, resulting in a 2.60-fold rise in AUC, accurately predicted by the rat PBPK model. Subsequently, the workflow of the rat PBPK model was applied to humans, creating a model capable of predicting DDIs between the two drugs in humans. Simulation from the human PBPK model indicated that nicardipine co-administration in humans resulted in a nearly unchanged AUC of saxagliptin, with an approximate 1.05-fold change, indicating no clinically significant changes and revealing a lack of direct translation of animal interaction results to humans. The animal-to-human PBPK model extrapolation used in this study could enhance the reliability of predicting drug interactions in clinical settings where DDI studies are challenging.
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Affiliation(s)
- Jeong-Min Lee
- Department of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea;
| | - Jin-Ha Yoon
- College of Pharmacy, Gachon University, Incheon 21936, Republic of Korea;
| | - Han-Joo Maeng
- College of Pharmacy, Gachon University, Incheon 21936, Republic of Korea;
| | - Yu Chul Kim
- Department of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea;
- Department of Pharmaceutical Engineering, Inje University, Gimhae 50834, Republic of Korea
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Storelli F, Ladumor MK, Liang X, Lai Y, Chothe PP, Enogieru OJ, Evers R, Unadkat JD. Toward improved predictions of pharmacokinetics of transported drugs in hepatic impairment: Insights from the extended clearance model. CPT Pharmacometrics Syst Pharmacol 2024; 13:118-131. [PMID: 37833845 PMCID: PMC10787213 DOI: 10.1002/psp4.13062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/04/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023] Open
Abstract
Hepatic impairment (HI) moderately (<5-fold) affects the systemic exposure (i.e., area under the plasma concentration-time curve [AUC]) of drugs that are substrates of the hepatic sinusoidal organic anion transporting polypeptide (OATP) transporters and are excreted unchanged in the bile and/or urine. However, the effect of HI on their AUC is much greater (>10-fold) for drugs that are also substrates of cytochrome P450 (CYP) 3A enzymes. Using the extended clearance model, through simulations, we identified the ratio of sinusoidal efflux clearance (CL) over the sum of metabolic and biliary CLs as important in predicting the impact of HI on the AUC of dual OATP/CYP3A substrates. Because HI may reduce hepatic CYP3A-mediated CL to a greater extent than biliary efflux CL, the greater the contribution of the former versus the latter, the greater the impact of HI on drug AUC ratio (AUCRHI ). Using physiologically-based pharmacokinetic modeling and simulation, we predicted relatively well the AUCRHI of OATP substrates that are not significantly metabolized (pitavastatin, rosuvastatin, valsartan, and gadoxetic acid). However, there was a trend toward underprediction of the AUCRHI of the dual OATP/CYP3A4 substrates fimasartan and atorvastatin. These predictions improved when the sinusoidal efflux CL of these two drugs was increased in healthy volunteers (i.e., before incorporating the effect of HI), and by modifying the directionality of its modulation by HI (i.e., increase or decrease). To accurately predict the effect of HI on AUC of hepatobiliary cleared drugs it is important to accurately predict all hepatobiliary pathways, including sinusoidal efflux CL.
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Affiliation(s)
- Flavia Storelli
- Department of PharmaceuticsUniversity of WashingtonSeattleWashingtonUSA
| | - Mayur K. Ladumor
- Department of PharmaceuticsUniversity of WashingtonSeattleWashingtonUSA
| | - Xiaomin Liang
- Drug Metabolism, Gilead Sciences Inc.Foster CityCaliforniaUSA
| | - Yurong Lai
- Drug Metabolism, Gilead Sciences Inc.Foster CityCaliforniaUSA
| | - Paresh P. Chothe
- Global Drug Metabolism and Pharmacokinetics, Takeda Development Center Americas, Inc.LexingtonMassachusettsUSA
| | | | - Raymond Evers
- Preclinical Sciences and Translational Safety, Janssen Research & Development, LLCSpring HousePennsylvaniaUSA
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Lancheros Porras KD, Alves IA, Novoa DMA. PBPK Modeling as an Alternative Method of Interspecies Extrapolation that Reduces the Use of Animals: A Systematic Review. Curr Med Chem 2024; 31:102-126. [PMID: 37031391 DOI: 10.2174/0929867330666230408201849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/03/2023] [Accepted: 02/03/2023] [Indexed: 04/10/2023]
Abstract
INTRODUCTION Physiologically based pharmacokinetic (PBPK) modeling is a computational approach that simulates the anatomical structure of the studied species and presents the organs and tissues as compartments interconnected by arterial and venous blood flows. AIM The aim of this systematic review was to analyze the published articles focused on the development of PBPK models for interspecies extrapolation in the disposition of drugs and health risk assessment, presenting to this modeling an alternative to reduce the use of animals. METHODS For this purpose, a systematic search was performed in PubMed using the following search terms: "PBPK" and "Interspecies extrapolation". The revision was performed according to PRISMA guidelines. RESULTS In the analysis of the articles, it was found that rats and mice are the most commonly used animal models in the PBPK models; however, most of the physiological and physicochemical information used in the reviewed studies were obtained from previous publications. Additionally, most of the PBPK models were developed to extrapolate pharmacokinetic parameters to humans and the main application of the models was for toxicity testing. CONCLUSION PBPK modeling is an alternative that allows the integration of in vitro and in silico data as well as parameters reported in the literature to predict the pharmacokinetics of chemical substances, reducing in large quantity the use of animals that are required in traditional studies.
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Cuquerella-Gilabert M, Reig-López J, Serna J, Rueda-Ferreiro A, Merino-Sanjuan M, Mangas-Sanjuan V, Sánchez-Herrero S. Phys-DAT: A physiologically-based pharmacokinetic model for unraveling the dissolution, transit and absorption processes using PhysPK®. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107929. [PMID: 38006685 DOI: 10.1016/j.cmpb.2023.107929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/11/2023] [Accepted: 11/13/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND AND OBJECTIVE In silico methods have become the key for efficiently testing and qualifying drug properties. Due to the complexity of the LADME processes and drug characteristics associated to oral drug absorption, there is a growing demand in the development of Physiologically-based Pharmacokinetic (PBPK) software with greater flexibility. Thus, the aims of this work are (i) to develop a mechanistic-based modeling framework of dissolution, transit and absorption (Phys-DAT) processes in the PhysPK platform and (ii) to assess the predictive power of the acausal MOOM methodology embedded in Phys-DAT versus reference ODE-based PBPK software. METHODS A PBPK model was developed including unreleased, undissolved and dissolved thermodynamic states of the drug. The gastrointestinal tract (GI) was represented by nine compartments and first-order transit kinetics was assumed for the drug fractions. Dissolution processes were described using solubility-independent or solubility-dependent mechanisms and pH effects. Linear transit and linear absorption mechanisms including gradual decrease absorption rate were considered to represent the passive diffusion process. Internal validation of the Phys-DAT model was performed through simulation-based analysis, considering different theoretical scenarios. External validation was carried out using in silico and in vivo data of GI segments and plasma concentrations. Both BCS I and II class drugs were included. RESULTS The model predicts plasma-concentration profiles of each compartment for undissolved, dissolved, and absorbed fractions using PhysPK® v.2.4.1. Internal and external validations demonstrate that the model aligned with the theoretical assumptions and accurately predicted Cmax, Tmax, and AUC 0-t for both BCS I and II drugs. Average Fold Error (AFE), Absolute Average Fold Error (AAFE), and Percent Prediction Error (PPE) calculations indicate good predictive performance, with predicted/observed ratios falling within the acceptable range. CONCLUSIONS Phys-DAT represents a mechanistic model for predicting oral absorption, including the dissolution, pH effect, transit, and absorption processes. PhysPK has shown to be a tool with strong prediction accuracy, similar to the obtained by ODE-based PBPK reference software, and the results obtained with the Phys-DAT model for oral administered drugs showed predictive reliability in healthy volunteers, setting the basis to determine the interchangeability of the acausal MOOM methodology with other modeling approaches.
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Affiliation(s)
- Marina Cuquerella-Gilabert
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia, Valencia, Spain; Simulation Department, Empresarios Agrupados Internacional S.A., Madrid, Spain
| | - Javier Reig-López
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia, Valencia, Spain
| | - Jenifer Serna
- Simulation Department, Empresarios Agrupados Internacional S.A., Madrid, Spain
| | | | - Matilde Merino-Sanjuan
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia, Valencia, Spain
| | - Victor Mangas-Sanjuan
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia, Valencia, Spain.
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Callegari E, Tse S, Doran AC, Goosen TC, Shaik N. Physiologically Based Pharmacokinetic Modeling of the Drug-Drug Interaction Between CYP3A4 Substrate Glasdegib and Moderate CYP3A4 Inducers in Lieu of a Clinical Study. J Clin Pharmacol 2024; 64:80-93. [PMID: 37731282 DOI: 10.1002/jcph.2348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 09/12/2023] [Indexed: 09/22/2023]
Abstract
Glasdegib (DAURISMO) is a hedgehog pathway inhibitor approved for the treatment of acute myeloid leukemia (AML). Cytochrome P450 3A4 (CYP3A4) has been identified as a major metabolism and clearance pathway for glasdegib. The role of CYP3A4 in the clearance of glasdegib has been confirmed with clinical drug-drug interaction (DDI) studies following the coadministration of glasdegib with the strong CYP3A4 inhibitor ketoconazole and the strong inducer rifampin. To evaluate potential drug interactions with CYP3A4 modulators, the coadministration of glasdegib with a moderate CYP3A4 inducer, efavirenz, was evaluated using physiologically based pharmacokinetic (PBPK) modeling using the Simcyp simulator. The glasdegib compound file was developed using measured physicochemical properties, data from human intravenous and oral pharmacokinetics, absorption, distribution, metabolism, and excretion studies, and in vitro reaction phenotyping results. The modeling assumptions, model parameters, and assignments of fractional CYP3A4 metabolism were verified using results from clinical pharmacokinetics (PK) and DDI studies with ketoconazole and rifampin. The verified glasdegib and efavirenz compound files, the latter of which was available in the Simcyp simulator, were used to estimate the potential impact of efavirenz on the PK of glasdegib. PBPK modeling predicted a glasdegib area under the concentration-time curve ratio of 0.45 and maximum plasma concentration ratio of 0.75 following coadministration with efavirenz. The PBPK results, in lieu of a formal clinical study, informed the drug label, with the recommendation to double the clinical dose of glasdegib when administered in conjunction with a moderate CYP3A4 inducer, followed by a resumption of the original dose 7 days post-discontinuation.
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Affiliation(s)
- Ernesto Callegari
- Medicine Design - Pharmacokinetics, Dynamics, and Metabolism, Pfizer Worldwide Research and Development, Pfizer Inc., Groton, CT, USA
| | - Susanna Tse
- Medicine Design - Pharmacokinetics, Dynamics, and Metabolism, Pfizer Worldwide Research and Development, Pfizer Inc., Groton, CT, USA
| | - Angela C Doran
- Medicine Design - Pharmacokinetics, Dynamics, and Metabolism, Pfizer Worldwide Research and Development, Pfizer Inc., Groton, CT, USA
| | - Theunis C Goosen
- Medicine Design - Pharmacokinetics, Dynamics, and Metabolism, Pfizer Worldwide Research and Development, Pfizer Inc., Groton, CT, USA
| | - Naveed Shaik
- Clinical Pharmacology and Bioanalytics, Pfizer Inc., La Jolla, CA, USA
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Verma A, Chauhan A, Awasthi A. Transcending Molecules: Paving the Way from Lab to Life in Drug Transport Innovation. Curr Drug Targets 2024; 25:445-448. [PMID: 38639289 DOI: 10.2174/0113894501305312240414073623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 03/19/2024] [Accepted: 03/27/2024] [Indexed: 04/20/2024]
Affiliation(s)
- Abhishek Verma
- Department of Pharmaceutics, ISF College of Pharmacy, Moga, Punjab, 142001, India
| | - Abhishek Chauhan
- Department of Pharmaceutics, ISF College of Pharmacy, Moga, Punjab, 142001, India
| | - Ankit Awasthi
- Department of Pharmaceutics, ISF College of Pharmacy, Moga, Punjab, 142001, India
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Morningstar-Kywi N, Morris DN, Romero RM, Haworth IS. Teaching of drug disposition using physiologically based pharmacokinetic modeling software: GastroPlus as an educational tool. ADVANCES IN PHYSIOLOGY EDUCATION 2023; 47:718-725. [PMID: 37471218 DOI: 10.1152/advan.00051.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/12/2023] [Accepted: 07/17/2023] [Indexed: 07/22/2023]
Abstract
Physiologically based pharmacokinetic (PBPK) modeling requires an understanding of chemical, physiologic, and pharmacokinetic principles. Active learning with PBPK modeling software (GastroPlus) may be useful to teach these scientific principles while also teaching software operation. To examine this issue, a graduate-level course was designed using learning objectives in science, software use, and PBPK model application. These objectives were taught through hands-on PBPK modeling to answer clinically relevant questions. Students demonstrated proficient use of software, based on their responses to these questions, and showed an improved understanding of scientific principles on a pre- and post-course assessment. These outcomes support the effectiveness of simultaneous teaching of interdependent software and science.NEW & NOTEWORTHY Physiologically based pharmacokinetic (PBPK) modeling is a major growth area in drug development, regulatory submissions, and clinical applications. There is a demand for experts in this area with multidisciplinary backgrounds. In this article, we describe a course designed to teach PBPK modeling and the underlying scientific principles in parallel.
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Affiliation(s)
- Noam Morningstar-Kywi
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, California, United States
- Simulations Plus, Inc., Lancaster, California, United States
| | - Denise N Morris
- Simulations Plus, Inc., Lancaster, California, United States
| | - Rebecca M Romero
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, California, United States
| | - Ian S Haworth
- Department of Pharmacology and Pharmaceutical Sciences, University of Southern California Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, Los Angeles, California, United States
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Madu SJ, Wang K, Chirumamilla SK, Turner DB, Steel PG, Li M. Assessing Dose-Exposure-Response Relationships of Miltefosine in Adults and Children using Physiologically-Based Pharmacokinetic Modeling Approach. Pharm Res 2023; 40:2983-3000. [PMID: 37816929 PMCID: PMC10746618 DOI: 10.1007/s11095-023-03610-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/18/2023] [Indexed: 10/12/2023]
Abstract
OBJECTIVES Miltefosine is the first and only oral medication to be successfully utilized as an antileishmanial agent. However, the drug is associated with differences in exposure patterns and cure rates among different population groups e.g. ethnicity and age (i.e., children v adults) in clinical trials. In this work, mechanistic population physiologically-based pharmacokinetic (PBPK) models have been developed to study the dose-exposure-response relationship of miltefosine in in silico clinical trials and evaluate the differences in population groups, particularly children and adults. METHODS The Simcyp population pharmacokinetics platform was employed to predict miltefosine exposure in plasma and peripheral blood mononuclear cells (PBMCs) in a virtual population under different dosing regimens. The cure rate of a simulation was based on the percentage of number of the individual virtual subjects with AUCd0-28 > 535 µg⋅day/mL in the virtual population. RESULTS It is shown that both adult and paediatric PBPK models of miltefosine can be developed to predict the PK data of the clinical trials accurately. There was no significant difference in the predicted dose-exposure-response of the miltefosine treatment for different simulated ethnicities under the same dose regime and the dose-selection strategies determined the clinical outcome of the miltefosine treatment. A lower cure rate of the miltefosine treatment in paediatrics was predicted because a lower exposure of miltefosine was simulated in virtual paediatric in comparison with adult virtual populations when they received the same dose of the treatment. CONCLUSIONS The mechanistic PBPK model suggested that the higher fraction of unbound miltefosine in plasma was responsible for a higher probability of failure in paediatrics because of the difference in the distribution of plasma proteins between adults and paediatrics. The developed PBPK models could be used to determine an optimal miltefosine dose regime in future clinical trials.
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Affiliation(s)
- Shadrack J Madu
- School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UK
| | - Ke Wang
- School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UK
| | | | - David B Turner
- Certara UK Limited, Simcyp Division, Sheffield, S1 2BJ, UK
| | - Patrick G Steel
- Department of Chemistry, Durham University, Durham, DH1 3LE, UK
| | - Mingzhong Li
- School of Pharmacy, De Montfort University, Leicester, LE1 9BH, UK.
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Wang L, Chen J, Chen W, Ruan Z, Lou H, Yang D, Jiang B. In silico prediction of bioequivalence of atorvastatin tablets based on GastroPlus™ software. BMC Pharmacol Toxicol 2023; 24:69. [PMID: 38017512 PMCID: PMC10685666 DOI: 10.1186/s40360-023-00689-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 09/18/2023] [Indexed: 11/30/2023] Open
Abstract
The prediction of intestinal absorption of various drugs based on computer simulations has been a reality. However, in vivo pharmacokinetic simulations and virtual bioequivalence evaluation based on GastroPlus™ have not been found. This study aimed to simulate plasma concentrations with different dissolution profiles and run population simulations to evaluate the bioequivalence of test and reference products of atorvastation using GastroPlus software. The dissolution profiles of the reference and test products of atorvastatin (20 mg tablets), and clinical plasma concentration-time data of the reference product were used for the simulations. The results showed that the simulated models were successfully established for atorvastatin tablets. Population simulation results indicated that the test formulation was bioequivalent to the reference formulation. The findings suggest that modelling is an essential tool to demonstrating the possibility of pharmacokinetic and bioequivalence for atorvastatin. It will contribute to understanding the potential risks during the development of generic products.
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Affiliation(s)
- Lu Wang
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China
| | - Jinliang Chen
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China
| | - Wenjun Chen
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China
| | - Zourong Ruan
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China
| | - Honggang Lou
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China
| | - Dandan Yang
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China
| | - Bo Jiang
- Center of Clinical Pharmacology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.
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Chen M, Du R, Zhang T, Li C, Bao W, Xin F, Hou S, Yang Q, Chen L, Wang Q, Zhu A. The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment. TOXICS 2023; 11:874. [PMID: 37888724 PMCID: PMC10611306 DOI: 10.3390/toxics11100874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/17/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023]
Abstract
Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.
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Affiliation(s)
- Mengting Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Ruihu Du
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Tao Zhang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Chutao Li
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Wenqiang Bao
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Fan Xin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Shaozhang Hou
- Department of Pathology, School of Basic Medical Sciences, Ningxia Medical University, Yinchuan 750004, China
| | - Qiaomei Yang
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Li Chen
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Qi Wang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
- Key Laboratory of State Administration of Traditional Chinese Medicine for Compatibility Toxicology, Beijing 100191, China
- Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, China
| | - An Zhu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
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Tsakalozou E, Mohamed MEF, Polak S, Heimbach T. Applications of Modeling and Simulation Approaches in Support of Drug Product Development of Oral Dosage Forms and Locally Acting Drug Products: a Symposium Summary. AAPS J 2023; 25:96. [PMID: 37783902 DOI: 10.1208/s12248-023-00862-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 09/16/2023] [Indexed: 10/04/2023] Open
Abstract
The number of modeling and simulation applications, including physiologically based pharmacokinetic (PBPK) models, physiologically based biopharmaceutics modeling (PBBM), and empirical models, has been constantly increasing along with the regulatory acceptance of these methodologies. While aiming at minimizing unnecessary human testing, these methodologies are used today to support the development and approval of novel drug products and generics. Modeling approaches are leveraged today for assessing drug-drug interaction, informing dose adjustments in renally or hepatically impaired patients, perform dose selection in pediatrics and pregnant women and diseased populations, and conduct biopharmaceutics-related assessments such as establish clinically relevant specifications for drug products and achieve quality assurance throughout the product life cycle. In the generics space, PBPK analyses are utilized toward virtual bioequivalence assessments within the scope of alternative bioequivalence approaches, product-specific guidance development, and food effect assessments among others. Case studies highlighting the evolving and expanding role of modeling and simulation approaches within the biopharmaceutics space were presented at the symposium titled "Model Informed Drug Development (MIDD): Role in Dose Selection, Vulnerable Populations, and Biowaivers - Chemical Entities" and Prologue "PBPK/PBBM to inform the Bioequivalence Safe Space, Food Effects, and pH-mediated DDIs" at the American Association of Pharmaceutical Scientists (AAPS) PharmSci 360 Annual Meeting in Boston, MA, on October 16-19, 2022, and are summarized here.
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Affiliation(s)
- Eleftheria Tsakalozou
- Division of Quantitative Methods and Modeling, Office of Research and Standards (ORS), Office of Generic Drugs (OGD), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), 10903 New Hampshire Avenue, Silver Spring, Maryland, USA.
| | | | - Sebastian Polak
- Certara UK, Simcyp Division, Sheffield, UK
- Jagiellonian University Medical College, Krakow, Poland
| | - Tycho Heimbach
- Pharmaceutical Sciences, MRL, Merck & Co., Inc, Rahway, New Jersey, 07065, USA
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Li X, Jusko WJ. Utility of Minimal Physiologically Based Pharmacokinetic Models for Assessing Fractional Distribution, Oral Absorption, and Series-Compartment Models of Hepatic Clearance. Drug Metab Dispos 2023; 51:1403-1418. [PMID: 37460222 PMCID: PMC10506700 DOI: 10.1124/dmd.123.001403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/13/2023] [Indexed: 09/16/2023] Open
Abstract
Minimal physiologically based pharmacokinetic (mPBPK) models are physiologically relevant, require less information than full PBPK models, and offer flexibility in pharmacokinetics (PK). The well-stirred hepatic model (WSM) is commonly used in PBPK, whereas the more plausible dispersion model (DM) poses computational complexities. The series-compartment model (SCM) mimics the DM but is easier to operate. This work implements the SCM and mPBPK models for assessing fractional tissue distribution, oral absorption, and hepatic clearance using literature-reported blood and liver concentration-time data in rats for compounds mainly cleared by the liver. Further handled were various complexities, including nonlinear hepatic binding and metabolism, differing absorption kinetics, and sites of administration. The SCM containing one to five (n) liver subcompartments yields similar fittings and provides comparable estimates for hepatic extraction ratio (ER), prehepatic availability (Fg ), and first-order absorption rate constants (ka ). However, they produce decreased intrinsic clearances (CLint ) and liver-to-plasma partition coefficients (Kph ) with increasing n as expected. Model simulations demonstrated changes in intravenous and oral PK profiles with alterations in Kph and ka and with hepatic metabolic zonation. The permeability (PAMPA P) of the various compounds well explained the fitted fractional distribution (fd ) parameters. The SCM and mPBPK models offer advantages in distinguishing systemic, extrahepatic, and hepatic clearances. The SCM allows for incorporation of liver zonation and is useful in assessing changes in internal concentration gradients potentially masked by similar blood PK profiles. Improved assessment of intraorgan drug concentrations may offer insights into active moieties driving metabolism, biliary excretion, pharmacodynamics, and hepatic toxicity. SIGNIFICANCE STATEMENT: The minimal physiologically based pharmacokinetic model and the series-compartment model are useful in assessing oral absorption and hepatic clearance. They add flexibility in accounting for various drug- or system-specific complexities, including fractional distribution, nonlinear binding and saturable hepatic metabolism, and hepatic zonation. These models can offer improved insights into the intraorgan concentrations that reflect physiologically active moieties often driving disposition, pharmacodynamics, and toxicity.
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Affiliation(s)
- Xiaonan Li
- Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, New York
| | - William J Jusko
- Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, New York
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Yang W, Lipert M, Nofsinger R. Current screening, design, and delivery approaches to address low permeability of chemically synthesized modalities in drug discovery and early clinical development. Drug Discov Today 2023; 28:103685. [PMID: 37356613 DOI: 10.1016/j.drudis.2023.103685] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/09/2023] [Accepted: 06/20/2023] [Indexed: 06/27/2023]
Abstract
A drug's permeability across biological membranes is a key property associated with the successful development of an orally absorbed drug candidate. Although a variety of methods are available for predicting and assessing permeability, some are more preferred than others at specific stages of drug discovery and development across the pharmaceutical industry. Permeability measurements may be interpreted differently depending on the chosen method. Herein, we present a refreshed perspective on the screening approaches and philosophy in permeability evaluation, from early drug discovery to early clinical development. Additionally, we review and discuss chemical design and drug delivery technologies that can be leveraged to overcome permeability challenges, which are increasingly being used with emerging modalities.
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Affiliation(s)
- Wenzhan Yang
- Advanced Drug Delivery, Pharmaceutical Sciences, R&D, AstraZeneca, Boston, USA.
| | - Maya Lipert
- Molecular Profiling and Drug Delivery, Small Molecule CMC Development, AbbVie, Inc., North Chicago, IL, USA
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Dancik Y, Mittapelly N, Puttrevu SK, Polak S. A novel physiologically based pharmacokinetic model of rectal absorption, evaluated and verified using clinical data on 10 rectally administered drugs. Int J Pharm 2023; 643:123273. [PMID: 37507097 DOI: 10.1016/j.ijpharm.2023.123273] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 07/30/2023]
Abstract
We present a physiologically based pharmacokinetic (PBPK) model simulating systemic drug concentrations following administration to the human rectum. Rectum physiology is parameterized based on literature data. The model utilizes in vitro release (IVRT) profiles from which drug mass transfer through the rectal fluid and tissue and into the systemic circulation are predicted. Due to a lack of data, rectal fluid and tissue absorption parameters are predicted either from colon absorption, with modifications relevant to rectal physiology, or optimized. The PBPK model is evaluated by simulating 29 clinical studies for 10 drugs. For 8 drugs (diazepam, diclofenac, indomethacin, naproxen, paracetamol, pentobarbital, phenobarbital and theophylline) the bias (average fold error, AFE) and precision (absolute average fold error, AAFE) of Cmax, AUC0-t and AUC0-inf simulations range from 0.87 to 2.22, indicating good agreement with observed values. For prochlorperazine and promethazine, the AFEs and AAFEs of Cmax predictions are 1.30 and 2.52, respectively. TheAUC0-t and AUC0-inf are overpredicted for both compounds(AFEs and AAFEs from 2.66 to 4.90). This results from a lack of reliable elimination data for prochlorperazine and the relevance of the IVRT profiles used in the promethazine model. The model paves the way for more mechanistic rectal drug absorption studies and virtual bioequivalence methods for rectal drug products.
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Affiliation(s)
- Yuri Dancik
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK.
| | - Naresh Mittapelly
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK
| | - Santosh K Puttrevu
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK
| | - Sebastian Polak
- Certara UK Limited, Simcyp Division, Level 2-Acero, 1 Concourse Way, Sheffield S1 2BJ, UK; Pharmacoepidemiology and Pharmacoeconomics Unit, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, 30-688 Krakow, Poland
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Leys K, Stroe MS, Annaert P, Van Cruchten S, Carpentier S, Allegaert K, Smits A. Pharmacokinetics during therapeutic hypothermia in neonates: from pathophysiology to translational knowledge and physiologically-based pharmacokinetic (PBPK) modeling. Expert Opin Drug Metab Toxicol 2023; 19:461-477. [PMID: 37470686 DOI: 10.1080/17425255.2023.2237412] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 05/13/2023] [Accepted: 07/13/2023] [Indexed: 07/21/2023]
Abstract
INTRODUCTION Perinatal asphyxia (PA) still causes significant morbidity and mortality. Therapeutic hypothermia (TH) is the only effective therapy for neonates with moderate to severe hypoxic-ischemic encephalopathy after PA. These neonates need additional pharmacotherapy, and both PA and TH may impact physiology and, consequently, pharmacokinetics (PK) and pharmacodynamics (PD). AREAS COVERED This review provides an overview of the available knowledge in PubMed (until November 2022) on the pathophysiology of neonates with PA/TH. In vivo pig models for this setting enable distinguishing the effect of PA versus TH on PK and translating this effect to human neonates. Available asphyxia pig models and methodological considerations are described. A summary of human neonatal PK of supportive pharmacotherapy to improve neurodevelopmental outcomes is provided. EXPERT OPINION To support drug development for this population, knowledge from clinical observations (PK data, real-world data on physiology), preclinical (in vitro and in vivo (minipig)) data, and molecular and cellular biology insights can be integrated into a predictive physiologically-based PK (PBPK) framework, as illustrated by the I-PREDICT project (Innovative physiology-based pharmacokinetic model to predict drug exposure in neonates undergoing cooling therapy). Current knowledge, challenges, and expert opinion on the future directions of this research topic are provided.
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Affiliation(s)
- Karen Leys
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences KU Leuven, Leuven, Belgium
| | - Marina-Stefania Stroe
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, Antwerp, Belgium
| | - Pieter Annaert
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences KU Leuven, Leuven, Belgium
- BioNotus GCV, Niel, Belgium
| | - Steven Van Cruchten
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Karel Allegaert
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
- Department of Hospital Pharmacy, Erasmus MC, GA, Rotterdam, The Netherlands
- Child and Youth Institute, KU Leuven, Leuven, Belgium
| | - Anne Smits
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
- Child and Youth Institute, KU Leuven, Leuven, Belgium
- Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium
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Jiang P, Chen T, Chu LF, Xu RP, Gao JT, Wang L, Liu Q, Tang L, Wan H, Li M, Ren HC. Enhancing drug-drug Interaction Prediction by Integrating Physiologically-Based Pharmacokinetic Model with Fraction Metabolized by CYP3A4. Expert Opin Drug Metab Toxicol 2023; 19:721-731. [PMID: 37746740 DOI: 10.1080/17425255.2023.2263358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 08/31/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Enhancing the precision of drug-drug interaction (DDI) prediction is essential for improving drug safety and efficacy. The aim is to identify the most effective fraction metabolized by CY3A4 (fm) for improving DDI prediction using physiologically based pharmacokinetic (PBPK) models. RESEARCH DESIGN AND METHODS The fm values were determined for 33 approved drugs using a human liver microsome for in vitro measurements and the ADMET Predictor software for in silico predictions. Subsequently, these fm values were integrated into PBPK models using the GastroPlus platform. The PBPK models, combined with a ketoconazole model, were utilized to predict AUCR (AUCcombo with ketoconazole/AUCdosing alone), and the accuracy of these predictions was evaluated by comparison with observed AUCR. RESULTS The integration of in vitro fm method demonstrates superior performance compared to the in silico fm method and fm of 100% method. Under the Guest-limits criteria, the integration of in vitro fm achieves an accuracy of 76%, while the in silico fm and fm of 100% methods achieve accuracies of 67% and 58%, respectively. CONCLUSIONS Our study highlights the importance of in vitro fm data to improve the accuracy of predicting DDIs and demonstrates the promising potential of in silico fm in predicting DDIs.
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Affiliation(s)
- Pin Jiang
- Department of DMPK, Shanghai Medicilon Inc, Shanghai, P. R. China
| | - Tao Chen
- Shanghai PharmoGo Co., Ltd, Shanghai, P. R. China
| | - Lin-Feng Chu
- Department of DMPK, Shanghai Medicilon Inc, Shanghai, P. R. China
| | - Ren-Peng Xu
- Department of DMPK, Shanghai Medicilon Inc, Shanghai, P. R. China
| | - Jin-Ting Gao
- Drug Discovery Department, GenFleet Therapeutics (Shanghai) Inc, Shanghai, P. R. China
| | - Li Wang
- Drug Discovery Department, GenFleet Therapeutics (Shanghai) Inc, Shanghai, P. R. China
| | - Qiang Liu
- Drug Discovery Department, GenFleet Therapeutics (Shanghai) Inc, Shanghai, P. R. China
| | - Lily Tang
- Drug Discovery Department, GenFleet Therapeutics (Shanghai) Inc, Shanghai, P. R. China
| | - Hong Wan
- Department of DMPK, Shanghai Medicilon Inc, Shanghai, P. R. China
| | - Ming Li
- Department of Cardiovascular Surgery, First Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R.China
| | - Hong-Can Ren
- Drug Discovery Department, GenFleet Therapeutics (Shanghai) Inc, Shanghai, P. R. China
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