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Khatri D, Felmingham B, Moore C, Lazaraki S, Stenta T, Collier L, Elliott DA, Metz D, Conyers R. Evaluating the evidence for genotype-informed Bayesian dosing of tacrolimus in children undergoing solid organ transplantation: A systematic literature review. Br J Clin Pharmacol 2024. [PMID: 39147586 DOI: 10.1111/bcp.16203] [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: 11/13/2023] [Revised: 07/04/2024] [Accepted: 07/18/2024] [Indexed: 08/17/2024] Open
Abstract
Tacrolimus, a calcineurin inhibitor, is a highly effective immunosuppressant used in solid organ transplantation (SOT). However, it is characterized by a narrow therapeutic range and high inter-patient variability in pharmacokinetics. Standard weight-based dosing followed by empiric dose titration is suboptimal in controlling drug concentrations, increasing risk of rejection or toxicity, particularly in the initial months post transplantation. This review explores the potential of combined pre-transplant genotyping and pharmacokinetic (PK) modelling to improve tacrolimus dosing in paediatric SOT recipients. A systematic search of Medline, Embase and Cochrane databases identified studies published between March 2013 and March 2023 that investigated genotype- and PK model-informed tacrolimus dosing in children post-SOT. The Newcastle-Ottawa Scale assessed study quality. Seven studies encompassing paediatric kidney, heart, liver and lung transplants reported using genotype and model-informed dosing. A combination of clinical and genetic factors significantly impacts tacrolimus clearance and thus initial dose recommendation. Body size, transplant organ and co-medications were consistently important, while either time post-transplant or haematocrit emerged in some studies. Several models were identified, however, with limitations evident in some and with absence of evidence for their effectiveness in optimizing initial and subsequent dosing. This review highlights the development of PK models in paediatric SOT that integrate genotype and clinical covariates to personalize early tacrolimus dosing. While promising, prospective studies are needed to validate and confirm their effectiveness in improving time to therapeutic concentrations and reducing under- or overexposure. This approach has the potential to optimize tacrolimus therapy in paediatric SOT, thereby improving outcomes.
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Affiliation(s)
- Dhrita Khatri
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
| | - Ben Felmingham
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
| | - Claire Moore
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Melbourne, VIC, Australia
| | - Smaro Lazaraki
- Health Sciences Library, Royal Melbourne Hospital, Melbourne Health, Australia
| | - Tayla Stenta
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
| | - Lane Collier
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
| | - David A Elliott
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Melbourne, VIC, Australia
| | - David Metz
- Department of Nephrology, The Royal Children's Hospital, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Department of Paediatrics, Monash University, Melbourne, VIC, Australia
| | - Rachel Conyers
- Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Melbourne, VIC, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Melbourne, VIC, Australia
- Children's Cancer Centre, The Royal Children's Hospital, Melbourne, VIC, Australia
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Verona P, Edwards J, Hubert K, Avorio F, Re VL, Di Stefano R, Carollo A, Johnson H, Provenzani A. Tacrolimus-Induced Neurotoxicity After Transplant: A Literature Review. Drug Saf 2024; 47:419-438. [PMID: 38353884 DOI: 10.1007/s40264-024-01398-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2024] [Indexed: 04/17/2024]
Abstract
Tacrolimus, a calcineurin inhibitor, is an immunosuppressant used globally to prevent rejection after organ transplantation. Although it significantly improves outcomes for solid organ transplant patients, it is associated with various side effects such as nephrotoxicity and neurotoxicity. Tacrolimus-induced neurotoxicity is frequently encountered in clinical practice and can present with a variety of symptoms that may occur even at therapeutic levels. Although tacrolimus-induced neurotoxicity is well documented, there is limited literature available on pharmacologic management. Twenty-eight case reports of tacrolimus-induced neurotoxicity were identified and analyzed in addition to other literature including reviews, retrospective studies, and animal model studies. The severity of cases of tacrolimus-induced neurotoxicity reported ranged from mild symptoms that could be managed with symptomatic treatment to conditions such as posterior reversible encephalopathy syndrome and chronic inflammatory demyelinating polyradiculoneuropathy that may require more immediate intervention. This information was utilized in addition to clinical experience to compile potential management options for prevention and treatment of neurotoxic adverse events. This review is limited by the utilization of primarily retrospective studies and case reports. The available literature on the subject is largely narrative and there are no guidelines on treatment of tacrolimus-induced neurotoxicity at the time of this research. This comprehensive review may guide further studies to investigate the pathophysiology of tacrolimus-induced neurotoxicity and to define patient-specific strategies for mitigation or minimization of neurotoxicity. This is especially important given that management of tacrolimus-induced neurotoxicity can include changes to immunosuppression that can result in an increased risk of rejection.
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Affiliation(s)
- Paige Verona
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jocelyn Edwards
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kassidy Hubert
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Federica Avorio
- Neurology Unit, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (ISMETT), Palermo, Italy
| | - Vincenzina Lo Re
- Neurology Unit, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (ISMETT), Palermo, Italy
| | - Roberta Di Stefano
- Clinical Pharmacy Service, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (ISMETT), Via E.Tricomi n. 5, 90127, Palermo, Italy
| | - Anna Carollo
- Clinical Pharmacy Service, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (ISMETT), Via E.Tricomi n. 5, 90127, Palermo, Italy
| | - Heather Johnson
- Department of Pharmacy and Therapeutics, University of Pittsburgh School of Pharmacy, 3501 Terrace Street, Pittsburgh, PA, USA
| | - Alessio Provenzani
- Clinical Pharmacy Service, Mediterranean Institute for Transplantation and Advanced Specialized Therapies (ISMETT), Via E.Tricomi n. 5, 90127, Palermo, Italy.
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Khamlek K, Komenkul V, Sriboonruang T, Wattanavijitkul T. Population pharmacokinetic models of tacrolimus in paediatric solid organ transplant recipients: A systematic review. Br J Clin Pharmacol 2024; 90:406-426. [PMID: 37714740 DOI: 10.1111/bcp.15909] [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: 07/01/2023] [Revised: 09/05/2023] [Accepted: 09/12/2023] [Indexed: 09/17/2023] Open
Abstract
AIMS This study aimed to provide up-to-date information on paediatric population pharmacokinetic models of tacrolimus and to identify factors influencing tacrolimus pharmacokinetic variability. METHODS Systematic searches in the Web of Science, PubMed, Scopus, Science Direct, Cochrane, EMBASE databases and reference lists of articles were conducted from inception to March 2023. All population pharmacokinetic studies of tacrolimus using nonlinear mixed-effect modelling in paediatric solid organ transplant patients were included. RESULTS Of the 21 studies reviewed, 62% developed from liver transplant recipients and 33% from kidney transplant recipients. Most studies used a 1-compartment model to describe tacrolimus pharmacokinetics. Body weight was a significant predictor for tacrolimus volume of distribution (Vd/F). The estimated Vd/F for 1-compartment models ranged from 20 to 1890 L, whereas the peripheral volume of distribution (Vp/F) for 2-compartment models was between 290 and 1520 L. Body weight, days post-transplant, CYP3A5 genotype or haematocrit were frequently reported as significant predictors of tacrolimus clearance. The estimated apparent clearance values range between 0.12 and 2.18 L/h/kg, with inter-individual variability from 13.5 to 110.0%. Only 29% of the studies assessed the generalizability of the models with external validation. CONCLUSION This review highlights the potential factors, modelling approaches and validation methods that impact tacrolimus pharmacokinetics in a paediatric population. The clinician could predict tacrolimus clearance based on body weight, CYP3A5 genotype, days post-transplant or haematocrit. Further research is required to determine the relationship between pharmacogenetics and tacrolimus pharmacodynamics in paediatric patients and confirm the applicability of nonlinear kinetics in this population.
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Affiliation(s)
- Kanyaporn Khamlek
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Virunya Komenkul
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Tatta Sriboonruang
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Thitima Wattanavijitkul
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand
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Bidu NS, Mattoso RJC, de Oliveira Santos OAC, Alves IA, Fernandes BJD, Couto RD. Suspicious of Acute Kidney Graft Rejection: Tacrolimus Pharmacokinetics Under Methylprednisolone Therapy. Curr Drug Res Rev 2024; 16:403-411. [PMID: 37861009 DOI: 10.2174/0125899775266172231004074317] [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: 06/27/2023] [Revised: 08/08/2023] [Accepted: 09/07/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND Acute rejection remains one of the main complications in the first months after transplantation and may influence long-term outcomes. Tacrolimus has proven its usefulness in solid organ transplants and its monitoring through the application of pharmacokinetic concepts to optimize individual drug therapy. OBJECTIVE This research proposes to evaluate the tacrolimus pharmacokinetic parameters in patients suspected of acute kidney graft rejection under methylprednisolone pulse therapy. METHODS Eleven adult tacrolimus-treated renal recipients were selected from a prospective, single-arm, single-center cohort study, with suspicion of acute rejection although in use of methylprednisolone pulses therapy. They were followed up for three months posttransplantation, being tacrolimus trough serum concentrations determined using a chemiluminescent magnetic immunoassay, and pharmacokinetic parameters were estimated by using a nonlinear mixed-effects model implemented by Monolix 2020R1. A tacrolimus trough serum concentration range of 8 to 12 ng.mL-1 was considered therapeutic. RESULTS Six patients showed acute cellular rejection, and two of them in addition had an antibody- mediated rejection. Tacrolimus trough serum concentration was below the reference range in eight patients. Most patients showed a high tacrolimus concentration intrapatient and pharmacokinetic parameters variability. CONCLUSION The obtained pharmacokinetics parameters helped in understanding the kidney recipient patients' tacrolimus behavior, assisting in the improvement of individual drug therapy and reducing the risk of acute rejection episodes.
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Affiliation(s)
- Nadielle Silva Bidu
- Biotechnology in Health and Investigative Medicine Postgraduate Program, Gonçalo Moniz Institute, Oswaldo Cruz Foundation (Fiocruz), Salvador, Bahia, Brazil
- Clinical Biochemistry Laboratory, Department of Clinical and Toxicological Analysis, Faculty of Pharmacy, Federal University of Bahia/UFBA, University Campus, Barão de Jeremoabo Street, Ondina, Salvador, Bahia, Brazil
| | | | - Otávio Augusto Carvalho de Oliveira Santos
- Pharmacy Postgraduate Program, Faculty of Pharmacy, Federal University of Bahia/UFBA, Salvador, Bahia, Brazil
- Clinical Laboratory, Hospital Ana Neri, Salvador, Bahia, Brazil
| | - Izabel Almeida Alves
- Department of Drug, Faculty of Pharmacy, Federal University of Bahia/UFBA, Salvador, Bahia, Brazil
- Pharmaceutical Science Postgraduate Program, Faculty of Pharmacy, State University of Bahia/UNEB, Salvador, Bahia, Brazil
| | - Bruno José Dumêt Fernandes
- Clinical Biochemistry Laboratory, Department of Clinical and Toxicological Analysis, Faculty of Pharmacy, Federal University of Bahia/UFBA, University Campus, Barão de Jeremoabo Street, Ondina, Salvador, Bahia, Brazil
| | - Ricardo David Couto
- Biotechnology in Health and Investigative Medicine Postgraduate Program, Gonçalo Moniz Institute, Oswaldo Cruz Foundation (Fiocruz), Salvador, Bahia, Brazil
- Clinical Biochemistry Laboratory, Department of Clinical and Toxicological Analysis, Faculty of Pharmacy, Federal University of Bahia/UFBA, University Campus, Barão de Jeremoabo Street, Ondina, Salvador, Bahia, Brazil
- Pharmacy Postgraduate Program, Faculty of Pharmacy, Federal University of Bahia/UFBA, Salvador, Bahia, Brazil
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Mohammed Ali Z, Meertens M, Fernández B, Fontova P, Vidal-Alabró A, Rigo-Bonnin R, Melilli E, Cruzado JM, Grinyó JM, Colom H, Lloberas N. CYP3A5*3 and CYP3A4*22 Cluster Polymorphism Effects on LCP-Tac Tacrolimus Exposure: Population Pharmacokinetic Approach. Pharmaceutics 2023; 15:2699. [PMID: 38140040 PMCID: PMC10747255 DOI: 10.3390/pharmaceutics15122699] [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: 10/09/2023] [Revised: 11/24/2023] [Accepted: 11/26/2023] [Indexed: 12/24/2023] Open
Abstract
The aim of the study is to develop a population pharmacokinetic (PopPK) model and to investigate the influence of CYP3A5/CYP3A4 and ABCB1 single nucleotide polymorphisms (SNPs) on the Tacrolimus PK parameters after LCP-Tac formulation in stable adult renal transplant patients. The model was developed, using NONMEM v7.5, from full PK profiles from a clinical study (n = 30) and trough concentrations (C0) from patient follow-up (n = 68). The PK profile of the LCP-Tac formulation was best described by a two-compartment model with linear elimination, parameterized in elimination (CL/F) and distributional (CLD/F) clearances and central compartment (Vc/F) and peripheral compartment (Vp/F) distribution volumes. A time-lagged first-order absorption process was characterized using transit compartment models. According to the structural part of the base model, the LCP-Tac showed an absorption profile characterized by two transit compartments and a mean transit time of 3.02 h. Inter-individual variability was associated with CL/F, Vc/F, and Vp/F. Adding inter-occasion variability (IOV) on CL/F caused a statistically significant reduction in the model minimum objective function MOFV (p < 0.001). Genetic polymorphism of CYP3A5 and a cluster of CYP3A4/A5 SNPs statistically significantly influenced Tac CL/F. In conclusion, a PopPK model was successfully developed for LCP-Tac formulation in stable renal transplant patients. CYP3A4/A5 SNPs as a combined cluster including three different phenotypes (high, intermediate, and poor metabolizers) was the most powerful covariate to describe part of the inter-individual variability associated with apparent elimination clearance. Considering this covariate in the initial dose estimation and during the therapeutic drug monitoring (TDM) would probably optimize Tac exposure attainments.
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Affiliation(s)
- Zeyar Mohammed Ali
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
- Biopharmaceutics and Pharmacokinetics Unit, Department of Pharmacy and Pharmaceutical Technology and Physical Chemistry, School of Pharmacy, University of Barcelona, 08007 Barcelona, Spain
| | - Marinda Meertens
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
- Biopharmaceutics and Pharmacokinetics Unit, Department of Pharmacy and Pharmaceutical Technology and Physical Chemistry, School of Pharmacy, University of Barcelona, 08007 Barcelona, Spain
| | - Beatriz Fernández
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
- Biopharmaceutics and Pharmacokinetics Unit, Department of Pharmacy and Pharmaceutical Technology and Physical Chemistry, School of Pharmacy, University of Barcelona, 08007 Barcelona, Spain
| | - Pere Fontova
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
| | - Anna Vidal-Alabró
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
| | - Raul Rigo-Bonnin
- Biochemistry Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain;
| | - Edoardo Melilli
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
| | - Josep M. Cruzado
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
| | - Josep M. Grinyó
- Department of Clinical Sciences, Medicine Unit, University of Barcelona, 08007 Barcelona, Spain;
| | - Helena Colom
- Biopharmaceutics and Pharmacokinetics Unit, Department of Pharmacy and Pharmaceutical Technology and Physical Chemistry, School of Pharmacy, University of Barcelona, 08007 Barcelona, Spain
| | - Nuria Lloberas
- Nephrology Department, Hospital Universitari de Bellvitge-IDIBELL, 08908 Barcelona, Spain; (Z.M.A.); (M.M.); (B.F.); (P.F.); (A.V.-A.); (E.M.); (J.M.C.)
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Stankevičiūtė K, Woillard JB, Peck RW, Marquet P, van der Schaar M. Bridging the Worlds of Pharmacometrics and Machine Learning. Clin Pharmacokinet 2023; 62:1551-1565. [PMID: 37803104 DOI: 10.1007/s40262-023-01310-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/19/2023] [Indexed: 10/08/2023]
Abstract
Precision medicine requires individualized modeling of disease and drug dynamics, with machine learning-based computational techniques gaining increasing popularity. The complexity of either field, however, makes current pharmacological problems opaque to machine learning practitioners, and state-of-the-art machine learning methods inaccessible to pharmacometricians. To help bridge the two worlds, we provide an introduction to current problems and techniques in pharmacometrics that ranges from pharmacokinetic and pharmacodynamic modeling to pharmacometric simulations, model-informed precision dosing, and systems pharmacology, and review some of the machine learning approaches to address them. We hope this would facilitate collaboration between experts, with complementary strengths of principled pharmacometric modeling and flexibility of machine learning leading to synergistic effects in pharmacological applications.
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Affiliation(s)
- Kamilė Stankevičiūtė
- Department of Computer Science and Technology, University of Cambridge, 15 JJ Thomson Avenue, Cambridge, CB3 0FD, UK
| | - Jean-Baptiste Woillard
- INSERM U1248 P&T, University of Limoges, 2 rue du Pr Descottes, 87000, Limoges, France.
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France.
| | - Richard W Peck
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- Pharma Research and Development, Roche Innovation Center, Basel, Switzerland
| | - Pierre Marquet
- INSERM U1248 P&T, University of Limoges, 2 rue du Pr Descottes, 87000, Limoges, France
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France
| | - Mihaela van der Schaar
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
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Tan SB, Kumar KS, Truong ATL, Tan LWJ, Chong LM, Gan TRX, Mali VP, Aw MM, Blasiak A, Ho D. Comparing the Performance of Multiple Small-Data Personalized Tacrolimus Dosing Models for Pediatric Liver Transplant: A Retrospective Study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083591 DOI: 10.1109/embc40787.2023.10341002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Tacrolimus is a potent immunosuppressant used after pediatric liver transplant. However, tacrolimus's narrow therapeutic window, reliance on physicians' experience for the dose titration, and intra- and inter-patient variability result in liver transplant patients falling out of the target tacrolimus trough levels frequently. Existing personalized dosing models based on the area-under-the-concentration over time curves require a higher frequency of blood draws than the current standard of care and may not be practically feasible. We present a small-data artificial intelligence-derived platform, CURATE.AI, that uses data from individual patients obtained once daily to model the dose and response relationship and identify suitable doses dynamically. Retrospective optimization using 6 models of CURATE.AI and data from 16 patients demonstrated good predictive performance and identified a suitable model for further investigations.Clinical Relevance- This study established and compared the predictive performance of 6 personalized tacrolimus dosing models for pediatric liver transplant patients and identified a suitable model with consistently good predictive performance based on data from pediatric liver transplant patients.
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Haverals L, Roosens L, Wouters K, Marquet P, Monchaud C, Massart A, Abramowicz D, Hellemans R. Does the Tacrolimus Trough Level Adequately Predict Drug Exposure in Patients Requiring a High Tacrolimus Dose? Transplant Direct 2023; 9:e1439. [PMID: 37009168 PMCID: PMC10065838 DOI: 10.1097/txd.0000000000001439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 11/08/2022] [Accepted: 12/01/2022] [Indexed: 04/04/2023] Open
Abstract
Tacrolimus (Tac) has a narrow therapeutic range. Dosing is generally targeted at Tac trough levels (C 0), notwithstanding conflicting reports on the correlation between Tac C 0 and systemic exposure measured by the area-under-the-concentration-over-time curve (AUC). The Tac dose required to meet the target C 0 varies highly among patients. We hypothesized that patients requiring a relatively high Tac dose for a certain C 0 may show a higher AUC. Methods We retrospectively analyzed data from 53 patients in which a 24-h Tac AUC24 estimation was performed at our center. Patients were divided into those taking a low (≤0.15 mg/kg) or high (>0.15 mg/kg) once-daily Tac dose. Multiple linear regression models were used to investigate if the association between C 0 and AUC24 changes according to dose level. Results Despite the large difference in mean Tac dose between the low- and high-dose group (7 versus 17 mg/d), C 0 levels were similar. However, the mean AUC24 was substantially higher in the high-dose group (320 ± 96 h·μg/L versus 255 ± 81 h·μg/L, P < 0.001). This difference remained significant after adjusting for age and race. For a same C 0, every 0.01 mg/kg increase in Tac dose resulted in an AUC24 increase of 3.59 h·μg/L. Conclusions This study challenges the general belief that C 0 levels are sufficiently reliable to estimate systemic drug exposure. We demonstrated that patients requiring a relatively high Tac dose to attain therapeutic C 0 levels have higher drug exposure and could therefore potentially be overdosed.
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Affiliation(s)
- Lien Haverals
- Department of Nephrology, Antwerp University Hospital, Edegem, Belgium
| | - Laurence Roosens
- Department of Clinical and Biological Sciences, Antwerp University Hospital, Edegem, Belgium
| | - Kristien Wouters
- Department of Statistics, Antwerp University Hospital, Edegem, Belgium
| | - Pierre Marquet
- Department of Pharmacology and Transplantation, University of Limoges, CHU Limoges, Limoges, France
| | - Caroline Monchaud
- Department of Pharmacology and Transplantation, University of Limoges, CHU Limoges, Limoges, France
| | - Annick Massart
- Department of Nephrology, Antwerp University Hospital, Edegem, Belgium
| | - Daniel Abramowicz
- Department of Nephrology, Antwerp University Hospital, Edegem, Belgium
- Laboratory of Experimental Medicine and Pediatrics and Member of the Infla-Med Centre of Excellence, University of Antwerp, Edegem, Belgium
| | - Rachel Hellemans
- Department of Nephrology, Antwerp University Hospital, Edegem, Belgium
- Laboratory of Experimental Medicine and Pediatrics and Member of the Infla-Med Centre of Excellence, University of Antwerp, Edegem, Belgium
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9
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Destere A, Marquet P, Labriffe M, Drici MD, Woillard JB. A Hybrid Algorithm Combining Population Pharmacokinetic and Machine Learning for Isavuconazole Exposure Prediction. Pharm Res 2023; 40:951-959. [PMID: 36991227 DOI: 10.1007/s11095-023-03507-y] [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: 11/20/2022] [Accepted: 03/21/2023] [Indexed: 03/31/2023]
Abstract
OBJECTIVES Maximum a posteriori Bayesian estimation (MAP-BE) based on a limited sampling strategy and a population pharmacokinetic (POPPK) model is used to estimate individual pharmacokinetic parameters. Recently, we proposed a methodology that combined population pharmacokinetic and machine learning (ML) to decrease the bias and imprecision in individual iohexol clearance prediction. The aim of this study was to confirm the previous results by developing a hybrid algorithm combining POPPK, MAP-BE and ML that accurately predicts isavuconazole clearance. METHODS A total of 1727 isavuconazole rich PK profiles were simulated using a POPPK model from the literature, and MAP-BE was used to estimate the clearance based on: (i) the full PK profiles (refCL); and (ii) C24h only (C24h-CL). Xgboost was trained to correct the error between refCL and C24h-CL in the training dataset (75%). C24h-CL as well as ML-corrected C24h-CL were evaluated in a testing dataset (25%) and then in a set of PK profiles simulated using another published POPPK model. RESULTS A strong decrease in mean predictive error (MPE%), imprecision (RMSE%) and the number of profiles outside ± 20% MPE% (n-out20%) was observed with the hybrid algorithm (decreased in MPE% by 95.8% and 85.6%; RMSE% by 69.5% and 69.0%; n-out20% by 97.4% and 100% in the training and testing sets, respectively. In the external validation set, the hybrid algorithm decreased MPE% by 96%, RMSE% by 68% and n-out20% by 100%. CONCLUSION The hybrid model proposed significantly improved isavuconazole AUC estimation over MAP-BE based on the sole C24h and may improve dose adjustment.
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Affiliation(s)
- Alexandre Destere
- Pharmacology and Transplantation, INSERM U1248, Université de Limoges, 2 Rue du Pr Descottes, 87000, Limoges, France
- Department of Pharmacology and Pharmacovigilance Center, Côte d'Azur University Medical Center, Nice, France
| | - Pierre Marquet
- Pharmacology and Transplantation, INSERM U1248, Université de Limoges, 2 Rue du Pr Descottes, 87000, Limoges, France
- Department of Pharmacology Toxicology and Pharmacovigilance, CHU de Limoges, Limoges, France
| | - Marc Labriffe
- Pharmacology and Transplantation, INSERM U1248, Université de Limoges, 2 Rue du Pr Descottes, 87000, Limoges, France
- Department of Pharmacology Toxicology and Pharmacovigilance, CHU de Limoges, Limoges, France
| | - Milou-Daniel Drici
- Department of Pharmacology and Pharmacovigilance Center, Côte d'Azur University Medical Center, Nice, France
| | - Jean-Baptiste Woillard
- Pharmacology and Transplantation, INSERM U1248, Université de Limoges, 2 Rue du Pr Descottes, 87000, Limoges, France.
- Department of Pharmacology Toxicology and Pharmacovigilance, CHU de Limoges, Limoges, France.
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10
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Application of machine learning to predict tacrolimus exposure in liver and kidney transplant patients given the MeltDose formulation. Eur J Clin Pharmacol 2023; 79:311-319. [PMID: 36564549 DOI: 10.1007/s00228-022-03445-5] [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: 10/04/2022] [Accepted: 12/15/2022] [Indexed: 12/25/2022]
Abstract
PURPOSE Machine Learning (ML) algorithms represent an interesting alternative to maximum a posteriori Bayesian estimators (MAP-BE) for tacrolimus AUC estimation, but it is not known if training an ML model using a lower number of full pharmacokinetic (PK) profiles (= "true" reference AUC) provides better performances than using a larger dataset of less accurate AUC estimates. The objectives of this study were: to develop and benchmark ML algorithms trained using full PK profiles to estimate MeltDose®-tacrolimus individual AUCs using 2 or 3 blood concentrations; and to compare their performance to MAP-BE. METHODS Data from liver (n = 113) and kidney (n = 97) transplant recipients involved in MeltDose-tacrolimus PK studies were used for the training and evaluation of ML algorithms. "True" AUC0-24 h was calculated for each patient using the trapezoidal rule on the full PK profile. ML algorithms were trained to estimate tacrolimus true AUC using 2 or 3 blood concentrations. Performances were evaluated in 2 external sets of 16 (renal) and 48 (liver) transplant patients. RESULTS Best estimation performances were obtained with the MARS algorithm and the following limited sampling strategies (LSS): predose (0), 8, and 12 h post-dose (rMPE = - 1.28%, rRMSE = 7.57%), or 0 and 12 h (rMPE = - 1.9%, rRMSE = 10.06%). In the external dataset, the performances of the final ML algorithms based on two samples in kidney (rMPE = - 3.1%, rRMSE = 11.1%) or liver transplant recipients (rMPE = - 3.4%, rRMSE = 9.86%) were as good as or better than those of MAP-BEs based on three time points. CONCLUSION The MARS ML models developed using "true" MeltDose®-tacrolimus AUCs yielded accurate individual estimations using only two blood concentrations.
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11
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Deprez S, Stove CP. Dried blood microsampling-assisted therapeutic drug monitoring of immunosuppressants: An overview. J Chromatogr A 2023; 1689:463724. [PMID: 36592482 DOI: 10.1016/j.chroma.2022.463724] [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: 10/02/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022]
Abstract
In the field of solid organ transplantation, chemotherapy and autoimmune disorders, treatment with immunosuppressant drugs requires intensive follow-up of the blood concentrations via therapeutic drug monitoring (TDM) because of their narrow therapeutic window and high intra- and inter-subject variability. This requires frequent hospital visits and venepunctures to allow the determination of these analytes, putting a high burden on the patients. In the context of patient-centric thinking, it is becoming increasingly established that at least part of these conventional blood draws could be replaced by microsampling, allowing home-sampling and increasing the quality of life for these patients. In this review we discuss the published methods - mostly using liquid chromatography coupled to tandem mass spectrometry - that have utilized (volumetric) dried blood samples as an alternative for conventional liquid whole blood for the TDM of immunosuppressant drugs. Furthermore, some pre-analytical considerations using DBS or volumetric alternatives are considered, as well as the applicability on clinical samples. The implementation status in clinical practice is also discussed, including (1) the cost-effectiveness of this approach compared to venepuncture, (2) the availability of multiplexed methods, (3) the status of harmonization and (4) patient perception. A brief perspective on potential future developments for the dried blood-based TDM of immunosuppressant drugs is provided, by considering how obstacles for the implementation of these strategies into clinical practice might be overcome.
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Affiliation(s)
- Sigrid Deprez
- Laboratory of Toxicology, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium
| | - Christophe P Stove
- Laboratory of Toxicology, Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg 460, 9000 Ghent, Belgium.
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12
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Can the Area Under the Curve/Trough Level Ratio Be Used to Optimize Tacrolimus Individual Dose Adjustment? Transplantation 2023; 107:e27-e35. [PMID: 36508648 DOI: 10.1097/tp.0000000000004405] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND The aim of this work was to evaluate, in a large data set of renal transplant recipients, the intraindividual variability of the area under the curve (AUC)/predose concentration (C0) ratio in comparison with that of AUC, C0, AUC/dose, and C0/dose. METHODS Patients with at least 2 tacrolimus AUC estimation requests were extracted from the Immunosuppressant Bayesian dose Adjustment website, and relative variations between 2 consecutive visits for the different metrics were calculated and compared. RESULTS Data from 1325 patients on tacrolimus (3827 measured C0 and estimated AUC) showed that the lowest mean relative variation between 2 consecutives visits was for the AUC/C0 ratio (95% confidence interval [CI] relative fold change = -43% to 44% for AUC/C0; 95% CI, -77% to 72% for AUC; 95% CI, -82% to 98% for AUC/dose; 95% CI, -81% to 80% for C0 and 95% CI, -94% to 117% for C0/dose. The correlation between 2 consecutive requests, whether close or far apart, was also best for the AUC/C0 ratio ( r = 0.33 and r = 0.34, respectively) in comparison with C0 ( r = 0.21 and r = 0.22, respectively) and AUC ( r = 0.19 and 0.28, respectively). Regression analysis between AUC0-24 and C0 showed that for some patients, the usual C0 targets translated into some very unusual AUC values. As the AUC/C0 ratio is quite stable during large periods, individualized C0 targets can be derived from the AUC targets, and an algorithm that estimates the individualized C0 was developed for situations in which prior AUC estimates are available or not. CONCLUSIONS In this study, we confirmed in a large data set that the AUC/C0 ratio yields low intraindividual variability, whereas C0 shows the largest, and we propose to calculate individualized C0 targets based on this ratio.
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13
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Zhu H, Wang M, Xiong X, Du Y, Li D, Wang Z, Ge W, Zhu Y. Plasma metabolomic profiling reveals factors associated with dose-adjusted trough concentration of tacrolimus in liver transplant recipients. Front Pharmacol 2022; 13:1045843. [PMID: 36386159 PMCID: PMC9659571 DOI: 10.3389/fphar.2022.1045843] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/13/2022] [Indexed: 07/30/2023] Open
Abstract
Inter- and intrapatient variability of tacrolimus exposure is a vital prognostic risk factor for the clinical outcome of liver transplantation. New factors or biomarkers characterizing tacrolimus disposition is essential for optimal dose prediction in recipients of liver transplant. The aim of the study was to identify potential plasma metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients by using a global metabolomic approach. A total of 693 plasma samples were collected from 137 liver transplant recipients receiving tacrolimus and regular therapeutic drug monitoring. Untargeted metabolomic analysis was performed by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. Univariate and multivariate analyses with a mixed linear model were conducted, and the results showed that the dose-adjusted tacrolimus trough concentration was associated with 31 endogenous metabolites, including medium- and long-chain acylcarnitines such as stearoylcarnitine (β = 0.222, p = 0.001), microbiota-derived uremic retention solutes such as indolelactic acid (β = 0.194, p = 0.007), bile acids such as taurohyodeoxycholic acid (β = -0.056, p = 0.002), and steroid hormones such as testosterone (β = 0.099, p = 0.001). A multiple linear mixed model including 11 metabolites and clinical information was established with a suitable predictive performance (correlation coefficient based on fixed effects = 0.64 and correlation coefficient based on fixed and random effects = 0.78). These data demonstrated that microbiota-derived uremic retention solutes, bile acids, steroid hormones, and medium- and long-chain acylcarnitines were the main metabolites associated with the dose-adjusted trough concentration of tacrolimus in liver transplant recipients.
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Affiliation(s)
- Huaijun Zhu
- Department of Pharmacology, School of Pharmacy, Fudan University, Shanghai, China
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Min Wang
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Xiaofu Xiong
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yao Du
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Danying Li
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Zhou Wang
- State Key Laboratory of Quality Research in Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Weihong Ge
- Department of Pharmacy, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Yizhun Zhu
- Department of Pharmacology, School of Pharmacy, Fudan University, Shanghai, China
- State Key Laboratory of Quality Research in Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
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14
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Zhang Q, Tian X, Chen G, Yu Z, Zhang X, Lu J, Zhang J, Wang P, Hao X, Huang Y, Wang Z, Gao F, Yang J. A Prediction Model for Tacrolimus Daily Dose in Kidney Transplant Recipients With Machine Learning and Deep Learning Techniques. Front Med (Lausanne) 2022; 9:813117. [PMID: 35712101 PMCID: PMC9197124 DOI: 10.3389/fmed.2022.813117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 04/22/2022] [Indexed: 11/13/2022] Open
Abstract
Tacrolimus is a major immunosuppressor against post-transplant rejection in kidney transplant recipients. However, the narrow therapeutic index of tacrolimus and considerable variability among individuals are challenges for therapeutic outcomes. The aim of this study was to compare different machine learning and deep learning algorithms and establish individualized dose prediction models by using the best performing algorithm. Therefore, among the 10 commonly used algorithms we compared, the TabNet algorithm outperformed other algorithms with the highest R2 (0.824), the lowest prediction error [mean absolute error (MAE) 0.468, mean square error (MSE) 0.558, and root mean square error (RMSE) 0.745], and good performance of overestimated (5.29%) or underestimated dose percentage (8.52%). In the final prediction model, the last tacrolimus daily dose, the last tacrolimus therapeutic drug monitoring value, time after transplantation, hematocrit, serum creatinine, aspartate aminotransferase, weight, CYP3A5, body mass index, and uric acid were the most influential variables on tacrolimus daily dose. Our study provides a reference for the application of deep learning technique in tacrolimus dose estimation, and the TabNet model with desirable predictive performance is expected to be expanded and applied in future clinical practice.
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Affiliation(s)
- Qiwen Zhang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Xueke Tian
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Guang Chen
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Ze Yu
- Beijing Medicinovo Technology Co. Ltd, Beijing, China
| | - Xiaojian Zhang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Jingli Lu
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Jinyuan Zhang
- Beijing Medicinovo Technology Co. Ltd, Beijing, China
| | - Peile Wang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
| | - Xin Hao
- Dalian Medicinovo Technology Co. Ltd, Dalian, China
| | - Yining Huang
- McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Zeyuan Wang
- Beijing Medicinovo Technology Co. Ltd, Beijing, China
| | - Fei Gao
- Beijing Medicinovo Technology Co. Ltd, Beijing, China
| | - Jing Yang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China
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15
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Methaneethorn J, Lohitnavy M, Onlamai K, Leelakanok N. Predictive Performance of Published Tacrolimus Population Pharmacokinetic Models in Thai Kidney Transplant Patients. Eur J Drug Metab Pharmacokinet 2021; 47:105-116. [PMID: 34817826 DOI: 10.1007/s13318-021-00735-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND AND OBJECTIVE Tacrolimus is a narrow therapeutic index drug with high pharmacokinetic variability, and several tacrolimus population pharmacokinetic (PopPK) models were developed to guide individualized drug dosing. These models, however, may not perform well in other clinical settings. Therefore, we aimed to assess the predictive ability of published tacrolimus PopPK models using a dataset of Thai kidney transplant patients. METHODS The external dataset was retrospectively collected from medical records of Bhumibol Adulyadej Hospital, Thailand. Published tacrolimus PopPK models were systematically searched from PubMed, Science Direct, CINAHL Complete, and Scopus databases. Models conducted using a nonlinear mixed-effects approach with covariate resemblance to our external dataset were selected. The external dataset consisted of Thai kidney transplant patients receiving oral immediate- or extended-release tacrolimus formulations twice or once daily, respectively. Accuracy and precision of predicted concentrations were evaluated using mean absolute prediction error (MAPE), root mean square error (RMSE), and goodness of fit plots. RESULTS Only three models produced acceptable population predictions with the MAPE of < 50%. By using the Bayesian posthoc estimate of individual pharmacokinetic parameters, all models well performed with the MAPE and RMSE of < 30% and 40%, respectively, except two models; one could not successfully converge and the other substantially underpredicted tacrolimus concentrations. CONCLUSION We evaluated ten tacrolimus PopPK models, and eight models resulted in satisfactorily individual predicted tacrolimus concentrations in Thai kidney transplant patients and may be used to aid tacrolimus dose adjustment along with a clinical judgment.
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Affiliation(s)
- Janthima Methaneethorn
- Pharmacokinetic Research Unit, Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, 65000, Thailand.
- Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, Thailand.
| | - Manupat Lohitnavy
- Pharmacokinetic Research Unit, Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, 65000, Thailand
- Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, Thailand
| | - Kamonwan Onlamai
- Department of Pharmacy, Bhumibol Adulyadej Hospital, Bangkok, Thailand
| | - Nattawut Leelakanok
- Department of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Burapha University, Chonburi, Thailand
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16
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Taddeo A, Prim D, Bojescu ED, Segura JM, Pfeifer ME. Point-of-Care Therapeutic Drug Monitoring for Precision Dosing of Immunosuppressive Drugs. J Appl Lab Med 2021; 5:738-761. [PMID: 32533157 DOI: 10.1093/jalm/jfaa067] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 04/03/2020] [Indexed: 01/15/2023]
Abstract
BACKGROUND Immunosuppressive drugs (ISD) are an essential tool in the treatment of transplant rejection and immune-mediated diseases. Therapeutic drug monitoring (TDM) for determination of ISD concentrations in biological samples is an important instrument for dose personalization for improving efficacy while reducing side effects. While currently ISD concentration measurements are performed at specialized, centralized facilities, making the process complex and laborious for the patient, various innovative technical solutions have recently been proposed for bringing TDM to the point-of-care (POC). CONTENT In this review, we evaluate current ISD-TDM and its value, limitations, and proposed implementations. Then, we discuss the potential of POC-TDM in the era of personalized medicine, and provide an updated review on the unmet needs and available technological solutions for the development of POC-TDM devices for ISD monitoring. Finally, we provide concrete suggestions for the generation of a meaningful and more patient-centric process for ISD monitoring. SUMMARY POC-based ISD monitoring may improve clinical care by reducing turnaround time, by enabling more frequent measurements in order to obtain meaningful pharmacokinetic data (i.e., area under the curve) faster reaction in case of problems and by increasing patient convenience and compliance. The analysis of the ISD-TDM field prompts the evolution of POC testing toward the development of fully integrated platforms able to support clinical decision-making. We identify 4 major areas requiring careful combined implementation: patient usability, data meaningfulness, clinicians' acceptance, and cost-effectiveness.
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Affiliation(s)
- Adriano Taddeo
- Institute of Life Technologies - School of Engineering, HES-SO//University of Applied Sciences, Western Switzerland, Sion, Switzerland
| | - Denis Prim
- Institute of Life Technologies - School of Engineering, HES-SO//University of Applied Sciences, Western Switzerland, Sion, Switzerland
| | - Elena-Diana Bojescu
- Institute of Life Technologies - School of Engineering, HES-SO//University of Applied Sciences, Western Switzerland, Sion, Switzerland
| | - Jean-Manuel Segura
- Institute of Life Technologies - School of Engineering, HES-SO//University of Applied Sciences, Western Switzerland, Sion, Switzerland
| | - Marc E Pfeifer
- Institute of Life Technologies - School of Engineering, HES-SO//University of Applied Sciences, Western Switzerland, Sion, Switzerland
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17
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Brooks E, Tett SE, Isbel NM, McWhinney B, Staatz CE. Evaluation of Bayesian Forecasting Methods for Prediction of Tacrolimus Exposure Using Samples Taken on Two Occasions in Adult Kidney Transplant Recipients. Ther Drug Monit 2021; 43:238-246. [PMID: 32932413 DOI: 10.1097/ftd.0000000000000814] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/21/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND Bayesian forecasting-based limited sampling strategies (LSSs) for tacrolimus have not been evaluated for the prediction of subsequent tacrolimus exposure. This study examined the predictive performance of Bayesian forecasting programs/services for the estimation of future tacrolimus area under the curve (AUC) from 0 to 12 hours (AUC0-12) in kidney transplant recipients. METHODS Tacrolimus concentrations were measured in 20 adult kidney transplant recipients, 1 month post-transplant, on 2 occasions one week apart. Twelve samples were taken predose and 13 samples were taken postdose at the specified times on the first and second sampling occasions, respectively. The predicted AUC0-12 (AUCpredicted) was estimated using Bayesian forecasting programs/services and data from both sampling occasions for each patient and compared with the fully measured AUC0-12 (AUCmeasured) calculated using the linear trapezoidal rule on the second sampling occasion. The bias (median percentage prediction error [MPPE]) and imprecision (median absolute prediction error [MAPE]) were determined. RESULTS Three programs/services were evaluated using different LSSs (C0; C0, C1, C3; C0, C1, C2, C4; and all available concentrations). MPPE and MAPE for the prediction of fully measured AUC0-12 were <15% for each program/service (with the exclusion of when only C0 was used), when using estimated AUC from data on the same (second) occasion. The MPPE and MAPE for the prediction of a future fully measured AUC0-12 were <15% for 2 programs/services (and for the third when participants who had a tacrolimus dose change between sampling days were excluded), when the occasion 1-AUCpredicted, using C0, C1, and C3, was compared with the occasion 2-AUCmeasured. CONCLUSIONS All 3 Bayesian forecasting programs/services evaluated had acceptable bias and imprecision for predicting a future AUC0-12, using tacrolimus concentrations at C0, C1, and C3, and could be used for the accurate prediction of tacrolimus exposure in adult kidney transplant recipients.
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Affiliation(s)
- Emily Brooks
- School of Medicine, The University of Queensland
| | - Susan E Tett
- School of Pharmacy, The University of Queensland
| | - Nicole M Isbel
- School of Medicine, The University of Queensland
- Department of Nephrology, The Princess Alexandra Hospital; and
| | - Brett McWhinney
- Department of Pathology, Royal Brisbane and Women's Hospital, Brisbane, Australia
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18
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Maldonado AQ, West-Thielke P, Joyal K, Rogers C. Advances in personalized medicine and noninvasive diagnostics in solid organ transplantation. Pharmacotherapy 2021; 41:132-143. [PMID: 33156560 DOI: 10.1002/phar.2484] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 09/29/2020] [Accepted: 10/08/2020] [Indexed: 12/13/2022]
Abstract
Personalized medicine has been a mainstay and in practice in transplant pharmacotherapy since the advent of the field. Decisions pertaining to the diagnosis, selection, and monitoring of transplant pharmacotherapy are aimed toward the individual, the allograft, and the overall immunologic needs of the patient. Recent advances in pharmacogenomics, noninvasive biomarkers, and artificial intelligence (AI) technologies have the promise of transforming the way we individualize treatment and monitor allograft function. Pharmacogenomic testing can provide clinicians with additional data that can minimize toxicity and maximize therapeutic dosing in high-risk patients, leading to more informed decisions that may decrease the risk of rejection and adverse outcomes related to immunosuppressive therapies. Development of noninvasive strategies to monitor allograft function may offer safer and more convenient methods to detect allograft injury. Cell free DNA and gene expression profiling offer the potential to serve as "liquid biopsies" minimizing the risk to patients and providing clinicians with useful molecular data that may help individualize immunosuppression and rejection treatment. Use of big data in transplant and novel AI platforms, such as the iBox, hold tremendous promise in providing clinicians a "glimpse into the future" thereby allowing for a more individualized approach to immunosuppressive therapy that may minimize future adverse outcomes. Advances in diagnostics, laboratory science, and AI have made the application of personalized medicine even more tailored for solid organ transplant recipients. In this perspective, we summarize the current and emerging tools available, literature supporting use, and the horizon for future personalization of transplantation.
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Affiliation(s)
| | | | - Kayla Joyal
- Lahey Hospital and Medical Center, Burlington, Massachusetts, USA
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19
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Catić-Đorđević A, Pavlović I, Spasić A, Stefanović N, Pavlović D, Damnjanović I, Mitić B, Veličković-Radovanović R. Assessment of pharmacokinetic mycophenolic acid clearance models using Monte Carlo numerical analysis. Xenobiotica 2021; 51:387-393. [PMID: 33416418 DOI: 10.1080/00498254.2020.1871532] [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: 10/22/2022]
Abstract
Previously, we performed population pharmacokinetic analysis and indicated age, mycophenolate mofetil (MMF)/mycophenolic acid (MPA) daily dose, and presence of nifedipine in patient therapy as significant predictors of MPA apparent clearance (CL/F) variability. This study aimed to determine the reliability of previously published population pharmacokinetic models derived from similar studies. Furthermore, this study investigated correspondence between chosen population models from the literature.By means of the Monte Carlo simulation method, pharmacokinetic models from different studies are simulated and analysed in the range of standard deviations of measured system parameters as well as the range of observed model parameters taken from the comparison studies.The 1000 numerical simulations were performed for every analysed model in order to calculate the most possible MPA CL/F values according to the expected values from the performed experiment. Fitting our results with other models showed how the presence of nifedipine makes difference in MPA CL/F values.By testing the data from selected studies into our model, a similar range of expected CL/F values was obtained, which may confirm the validity of our model. The results of our population pharmacokinetic study are partially applicable in models by other researchers.
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Affiliation(s)
| | - Ivan Pavlović
- Faculty of Mechanical Engineering, University of Nis, Nis, Serbia
| | - Ana Spasić
- Faculty of Medicine, University of Nis, Nis, Serbia
| | | | | | | | - Branka Mitić
- Faculty of Medicine, University of Nis, Nis, Serbia.,Clinic of Nephrology, Clinical Center Nis, Nis, Serbia
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20
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Woillard J, Labriffe M, Debord J, Marquet P. Tacrolimus Exposure Prediction Using Machine Learning. Clin Pharmacol Ther 2021; 110:361-369. [DOI: 10.1002/cpt.2123] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 11/13/2020] [Indexed: 11/05/2022]
Affiliation(s)
- Jean‐Baptiste Woillard
- University of LimogesIPPRITT Limoges France
- INSERMIPPRITTU1248 Limoges France
- Department of Pharmacology and Toxicology CHU Limoges Limoges France
| | - Marc Labriffe
- University of LimogesIPPRITT Limoges France
- INSERMIPPRITTU1248 Limoges France
- Department of Pharmacology and Toxicology CHU Limoges Limoges France
| | - Jean Debord
- University of LimogesIPPRITT Limoges France
- INSERMIPPRITTU1248 Limoges France
- Department of Pharmacology and Toxicology CHU Limoges Limoges France
| | - Pierre Marquet
- University of LimogesIPPRITT Limoges France
- INSERMIPPRITTU1248 Limoges France
- Department of Pharmacology and Toxicology CHU Limoges Limoges France
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21
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De Sutter PJ, Gasthuys E, Van Braeckel E, Schelstraete P, Van Biervliet S, Van Bocxlaer J, Vermeulen A. Pharmacokinetics in Patients with Cystic Fibrosis: A Systematic Review of Data Published Between 1999 and 2019. Clin Pharmacokinet 2020; 59:1551-1573. [DOI: 10.1007/s40262-020-00932-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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22
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Leino AD, Pai MP. Maintenance Immunosuppression in Solid Organ Transplantation: Integrating Novel Pharmacodynamic Biomarkers to Inform Calcineurin Inhibitor Dose Selection. Clin Pharmacokinet 2020; 59:1317-1334. [PMID: 32720300 DOI: 10.1007/s40262-020-00923-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Calcineurin inhibitors, the primary immunosuppressive therapy used to prevent alloreactivity of transplanted organs, have a narrow therapeutic index. Currently, treatment is individualized based on clinical assessment of the risk of rejection or toxicity guided by trough concentration monitoring. Advances in immune monitoring have identified potential markers that may have value in understanding calcineurin inhibitor pharmacodynamics. Integration of these markers has the potential to complement therapeutic drug monitoring. Existing pharmacokinetic-pharmacodynamic (PK-PD) data is largely limited to correlation between the biomarker and trough concentrations at single time points. Immune related gene expression currently has the most evidence supporting PK-PD integration. Novel biomarker-based approaches to pharmacodynamic monitoring including development of enhanced PK-PD models are proposed to realize the full clinical benefit.
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Affiliation(s)
- Abbie D Leino
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, 428 Church Street, Rm 3569, Ann Arbor, MI, 48109, USA
| | - Manjunath P Pai
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, 428 Church Street, Rm 3569, Ann Arbor, MI, 48109, USA.
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23
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Riff C, Besombes J, Gatault P, Barbet C, Büchler M, Blasco H, Halimi JM, Barin-Le Guellec C, Benz-de Bretagne I. Assessment of the glomerular filtration rate (GFR) in kidney transplant recipients using Bayesian estimation of the iohexol clearance. Clin Chem Lab Med 2020; 58:577-587. [PMID: 31926067 DOI: 10.1515/cclm-2019-0904] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 11/17/2019] [Indexed: 11/15/2022]
Abstract
Background Plasma iohexol clearance (CLiohexol) is a reference technique for glomerular filtration rate (GFR) determination. In routine practice, CLiohexol is calculated using one of several formulas, which have never been evaluated in kidney transplant recipients. We aimed to model iohexol pharmacokinetics in this population, evaluate the predictive performance of three simplified formulas and evaluate whether a Bayesian algorithm improves CLiohexol estimation. Methods After administration of iohexol, six blood samples were drawn from 151 patients at various time points. The dataset was split into two groups, one to develop the population pharmacokinetic (POPPK) model (n = 103) and the other (n = 48) to estimate the predictive performances of the various GFR estimation methods. GFR reference values (GFRref) in the validation dataset were obtained by non-compartmental pharmacokinetic (PK) analysis. Predictive performances of each method were evaluated in terms of bias (ME), imprecision (root mean square error [RMSE]) and number of predictions out of the ±10% or 15% error interval around the GFRref. Results A two-compartment model best fitted the data. The Bayesian estimator with samples drawn at 30, 120 and 270 min allowed accurate prediction of GFRref (ME = 0.47%, RMSE = 3.42%), as did the Brøchner-Mortensen (BM) formula (ME = - 0.0425%, RMSE = 3.40%). With both methods, none of the CL estimates were outside the ±15% interval and only 2.4% were outside the ±10% for the BM formula (and none for the Bayesian estimator). In patients with GFR ≤30 mL/min/1.73 m2, the BM formula performed very well, while the Bayesian method could not be evaluated in depth due to too small a number of patients with adequate sampling times. Conclusions GFR can be estimated with acceptable accuracy in kidney transplant patients using the BM formula, but also using a Bayesian algorithm.
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Affiliation(s)
- Camille Riff
- Service de Pharmacologie et Toxicologie, CHU de Tours, Tours, France
| | - Joevin Besombes
- Laboratoire de Biochimie et de Biologie Moléculaire, CHU de Tours, Tours, France
| | - Philippe Gatault
- Service de Néphrologie, Transplantation rénale et Immunologie, CHU de Tours, Tours, France
- EA4245, Université de Tours, Tours, France
- FHU SUPPORT, Tours, France
| | - Christelle Barbet
- Service de Néphrologie, Transplantation rénale et Immunologie, CHU de Tours, Tours, France
| | - Matthias Büchler
- Service de Néphrologie, Transplantation rénale et Immunologie, CHU de Tours, Tours, France
- EA4245, Université de Tours, Tours, France
- FHU SUPPORT, Tours, France
| | - Hélène Blasco
- Laboratoire de Biochimie et de Biologie Moléculaire, CHU de Tours, Tours, France
- UMR INSERM U1253, Université de Tours, Tours, France
| | - Jean-Michel Halimi
- Service de Néphrologie, Transplantation rénale et Immunologie, CHU de Tours, Tours, France
- EA4245, Université de Tours, Tours, France
- FHU SUPPORT, Tours, France
| | - Chantal Barin-Le Guellec
- Laboratoire de Biochimie et de Biologie Moléculaire, CHU de Tours, Tours, France
- FHU SUPPORT, Tours, France
- INSERM U1248, IPPRITT, Université de Limoges, Limoges, France
| | - Isabelle Benz-de Bretagne
- Laboratoire de Biochimie et de Biologie Moléculaire, CHU de Tours, Tours, France
- UMR INSERM U1253, Université de Tours, Tours, France
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24
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Oberbauer R, Bestard O, Furian L, Maggiore U, Pascual J, Rostaing L, Budde K. Optimization of tacrolimus in kidney transplantation: New pharmacokinetic perspectives. Transplant Rev (Orlando) 2020; 34:100531. [PMID: 31955920 DOI: 10.1016/j.trre.2020.100531] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 11/05/2019] [Accepted: 12/08/2019] [Indexed: 02/07/2023]
Abstract
Tacrolimus is the cornerstone of immunosuppressive therapy after kidney transplantation (KT), but its use is complicated by a narrow therapeutic index and high inter- and intra-patient pharmacokinetic variability. There are three available oral formulations of tacrolimus: immediate-release tacrolimus (IR-Tac), extended-release tacrolimus (ER-Tac) and a MeltDose® (LCPT) formulation, the latter favoring a prolonged drug release and increased bioavailability. The time-concentration curves of these formulations are different. Compared with IR-Tac and ER-Tac, LCPT has a relatively flat pharmacokinetic profile with less fluctuation between trough and peak exposures, and a delayed peak concentration. This translates to a more stable delivery of tacrolimus and may alleviate the risk of underexposure and allograft rejection or overexposure and toxicity. The once-daily formulation of both ER-TAC and LCPT may also offer a potential advantage on patient adherence. Fast metabolizers of tacrolimus, the elderly, and human leukocyte antigen-sensitized patients are at risk of poorer outcomes after KT, possibly associated with a different exhibited pharmacokinetics of tacrolimus or different requirements in terms of exposure. Simple, practical strategies are needed to identify patients at risk of suboptimal KT outcomes and those who would benefit from a more proactively personalized approach to tacrolimus treatment. This review aims to increase awareness of the link between the pharmacokinetics of oral tacrolimus formulations and the clinical needs of patients after KT, particularly among those who have clinically significant pharmacokinetic variation of tacrolimus.
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Affiliation(s)
- Rainer Oberbauer
- Department of Nephrology, Medical University of Vienna, Vienna, Austria
| | - Oriol Bestard
- Kidney Transplant Unit, Nephrology department, Bellvitge University Hospital, Barcelona, Spain
| | - Lucrezia Furian
- Kidney and Pancreas Transplantation Unit, Department of Surgical, Oncological and Gastroenterological Sciences, University of Padova, Italy
| | - Umberto Maggiore
- Kidney and Kidney-Pancreas Transplant Unit (Department of Nephrology), Parma University Hospital, Parma, Italy
| | - Julio Pascual
- Department of Nephrology, Hospital del Mar, Barcelona, Spain
| | - Lionel Rostaing
- Nephrology and Transplantation Department, CHU Grenoble, Grenoble, France
| | - Klemens Budde
- Department of Nephrology, Internal Intensive Care Medicine, Campus Charité Mitte, Berlin, Germany.
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25
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Nanga TM, Doan TTP, Marquet P, Musuamba FT. Toward a robust tool for pharmacokinetic-based personalization of treatment with tacrolimus in solid organ transplantation: A model-based meta-analysis approach. Br J Clin Pharmacol 2019; 85:2793-2823. [PMID: 31471970 DOI: 10.1111/bcp.14110] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 07/31/2019] [Accepted: 08/06/2019] [Indexed: 02/07/2023] Open
Abstract
AIMS The objective of this study is to develop a generic model for tacrolimus pharmacokinetics modelling using a meta-analysis approach, that could serve as a first step towards a prediction tool to inform pharmacokinetics-based optimal dosing of tacrolimus in different populations and indications. METHODS A systematic literature review was performed and a meta-model developed with NONMEM software using a top-down approach. Historical (previously published) data were used for model development and qualification. In-house individual rich and sparse tacrolimus blood concentration profiles from adult and paediatric kidney, liver, lung and heart transplant patients were used for model validation. Model validation was based on successful numerical convergence, adequate precision in parameter estimation, acceptable goodness of fit with respect to measured blood concentrations with no indication of bias, and acceptable performance of visual predictive checks. External validation was performed by fitting the model to independent data from 3 external cohorts and remaining previously published studies. RESULTS A total of 76 models were found relevant for meta-model building from the literature and the related parameters recorded. The meta-model developed using patient level data was structurally a 2-compartment model with first-order absorption, absorption lag time and first-time varying elimination. Population values for clearance, intercompartmental clearance, central and peripheral volume were 22.5 L/h, 24.2 L/h, 246.2 L and 109.9 L, respectively. The absorption first-order rate and the lag time were fixed to 3.37/h and 0.33 hours, respectively. Transplanted organ and time after transplantation were found to influence drug apparent clearance whereas body weight influenced both the apparent volume of distribution and the apparent clearance. The model displayed good results as regards the internal and external validation. CONCLUSION A meta-model was successfully developed for tacrolimus in solid organ transplantation that can be used as a basis for the prediction of concentrations in different groups of patients, and eventually for effective dose individualization in different subgroups of the population.
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Affiliation(s)
- Tom M Nanga
- INSERM UMR 1248, Université de Limoges, FHU support, Limoges Cédex, 87025, France
| | - Thao T P Doan
- INSERM UMR 1248, Université de Limoges, FHU support, Limoges Cédex, 87025, France
| | - Pierre Marquet
- INSERM UMR 1248, Université de Limoges, FHU support, Limoges Cédex, 87025, France
| | - Flora T Musuamba
- Federal Agency for Medicines and Health Products, Brussels, Belgium.,Faculté des sciences pharmaceutiques, Université de Lubumbashi, Lubumbashi, Democratic Republic of the Congo
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26
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Åsberg A, Bjerre A, Almaas R, Luis-Lima S, Robertsen I, Salvador CL, Porrini E, Schwartz GJ, Hartmann A, Bergan S. Measured GFR by Utilizing Population Pharmacokinetic Methods to Determine Iohexol Clearance. Kidney Int Rep 2019; 5:189-198. [PMID: 32043033 PMCID: PMC7000849 DOI: 10.1016/j.ekir.2019.11.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 10/29/2019] [Accepted: 11/25/2019] [Indexed: 11/29/2022] Open
Abstract
Introduction There is an increasing demand for accurately measured glomerular filtration rate (GFR). Iohexol serum clearance has become a new gold standard, but it is challenging when GFR is low and 24-hour sampling is required for accurate results. The primary aim of this study was to develop an iohexol pharmacokinetic population model for accurate determination of individual GFR using limited sampling for up to 5 hours also when renal function is <40 ml/min. Methods A nonparametric iohexol population pharmacokinetic model was developed with rich data from 176 patients. In a validation cohort of 43 patients, a model-determined GFR (iohexol clearance) using different limited sampling strategies for up to 5 hours was compared with the strategy currently used in routine care, a log-linear 2-point method. In all, 1526 iohexol concentrations were used, from patients ranging in age from 1 to 82 years and GFR from 14 to 149 ml/min. Results The clinical 2-point method showed insufficient agreement compared with reference values; 15% of GFR values had an error of greater than ±10% even when sampling for 24 hours when estimating GFR <40 ml/min per 1.73 m2 (standard procedure). Restricted sampling the first 5 hours with the population model required 4 samples to determine GFR accurately. This strategy showed excellent agreement with the reference; <3% of GFR values had an error greater than ±10 %. Conclusion Using an iohexol population pharmacokinetic model allows for accurate determination of GFR within 5 hours when applying 4 optimally timed samples, even in patients with GFR <40 ml/min.
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Affiliation(s)
- Anders Åsberg
- Department of Transplantation, Oslo University Hospital-Rikshospitalet, Oslo, Norway.,Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Anna Bjerre
- Division of Paediatric and Adolescent Medicine, Oslo University Hospital-Rikshospitalet, Oslo, Norway.,Department of Pediatrics, University of Rochester, Rochester, New York, USA
| | - Runar Almaas
- Division of Paediatric and Adolescent Medicine, Oslo University Hospital-Rikshospitalet, Oslo, Norway.,Department of Pediatric Research, Oslo University Hospital, Oslo, Norway
| | - Sergio Luis-Lima
- Internal Medicine Department, Hospital Universitario de Canarias, Tenerife, Spain
| | - Ida Robertsen
- Department of Pharmacy, University of Oslo, Oslo, Norway
| | | | - Esteban Porrini
- Internal Medicine Department, Hospital Universitario de Canarias, Tenerife, Spain
| | - George J Schwartz
- Department of Pediatrics, University of Rochester, Rochester, New York, USA
| | - Anders Hartmann
- Department of Transplantation, Oslo University Hospital-Rikshospitalet, Oslo, Norway
| | - Stein Bergan
- Department of Pharmacy, University of Oslo, Oslo, Norway.,Department of Medical Biochemistry, Oslo University Hospital-Rikshospitalet, Oslo, Norway
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27
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A Novel, Dose-Adjusted Tacrolimus Trough-Concentration Model for Predicting and Estimating Variance After Kidney Transplantation. Drugs R D 2019; 19:201-212. [PMID: 31073875 PMCID: PMC6544741 DOI: 10.1007/s40268-019-0271-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Background and Objective Given that a high intrapatient variability (IPV) of tacrolimus whole blood concentration increases the risk for a poor kidney transplant outcome, some experts advocate routine IPV monitoring for detection of high-risk patients. However, attempts to estimate the variance of tacrolimus trough concentrations (TTC) are limited by the need for patients to receive a fixed dose over time and/or the use of linear statistical models. A goal of this study is to overcome the current limitations through the novel application of statistical methodology generalizing the relationship between TTC and dose through the use of nonparametric functional regression modeling. Methods With TTC as a response and dose as a covariate, the model employs an unknown bivariate function, allowing for the potentially complex, nonlinear relationship between the two parameters. A dose-adjusted variance of TTC is then derived based on standard functional principal component analysis (FPCA). To assess the model, it was compared against an FPCA-based model and linear mixed-effects models using prediction error, bias, and coverage probabilities for simulated data as well as phase III data from the Astellas new drug application studies for extended-release tacrolimus. Results Our numerical investigation indicates that the new model better predicts dose-adjusted TTCs compared with the prediction of linear mixed effects models. Estimated coverage probabilities also indicate that the new model accurately accounts for the variance of TTC during the periods of large fluctuation in dose, whereas the linear mixed effects model consistently underestimates the coverage probabilities because of the inaccurate characterization of TTC fluctuation. Conclusion This is the first known application of a functional regression model to assess complex relationships between TTC and dose in a real clinical setting. This new method has applicability in future clinical trials including real-world data sets due to flexibility of the nonparametric modeling approach. Electronic supplementary material The online version of this article (10.1007/s40268-019-0271-2) contains supplementary material, which is available to authorized users.
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28
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Tacrolimus Can Be Reliably Measured With Volumetric Absorptive Capillary Microsampling Throughout the Dose Interval in Renal Transplant Recipients. Ther Drug Monit 2019; 41:607-614. [DOI: 10.1097/ftd.0000000000000655] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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29
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Riva N, Woillard JB, Distefano M, Moragas M, Dip M, Halac E, Cáceres Guido P, Licciardone N, Mangano A, Bosaleh A, de Davila MT, Schaiquevich P, Imventarza O. Identification of Factors Affecting Tacrolimus Trough Levels in Latin American Pediatric Liver Transplant Patients. Liver Transpl 2019; 25:1397-1407. [PMID: 31102573 DOI: 10.1002/lt.25495] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Accepted: 04/26/2019] [Indexed: 12/13/2022]
Abstract
Tacrolimus is the cornerstone in pediatric liver transplant immunosuppression. Despite close monitoring, fluctuations in tacrolimus blood levels affect safety and efficacy of immunosuppressive treatments. Identifying the factors related to the variability in tacrolimus exposure may be helpful in tailoring the dose. The aim of the present study was to characterize the clinical, pharmacological, and genetic variables associated with systemic tacrolimus exposure in pediatric liver transplant patients. De novo transplant patients with a survival of more than 1 month were considered for inclusion and were genotyped for cytochrome P450 3A5 (CYP3A5). Peritransplant clinical factors and laboratory covariates were recorded retrospectively between 1 month and 2 years after transplant, including alanine aminotransferase (ALT), aspartate aminotransferase, hematocrit, and tacrolimus predose steady-state blood concentrations collected 12 hours after tacrolimus dosing. A linear mixed effect (LME) model was used to assess the association of these factors and the log-transformed tacrolimus dose-normalized trough concentration (logC0/D) levels. Bootstrapping was used to internally validate the final model. External validation was performed in an independent group of patients who matched the original population. The developed LME model described that logC0/D increases with increases in time after transplant (β = 0.019, 95% confidence interval [CI], 0.010-0.028) and ALT values (β = 0.00030, 95% CI, 0.00002-0.00056), whereas logC0/D is significantly lower in graft CYP3A5 expressers compared with nonexpressers (β = -0.349, 95% CI, -0.631 to -0.062). In conclusion, donor CYP3A5 genotype, time after transplant, and ALT values are associated with tacrolimus disposition between 1 month and 2 years after transplant. A better understanding of tacrolimus exposure is essential to minimize the occurrence of an out-of-range therapeutic window that may lead to adverse drug reactions or acute rejection.
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Affiliation(s)
- Natalia Riva
- Unit of Clinical Pharmacokinetics, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Jean-Baptiste Woillard
- Department of Pharmacology and Toxicology, University of Limoges, Centre Hospitalier Universitaire Limoges, INSERM, IPPRITT, U1248, Limoges, France
| | - Maximiliano Distefano
- Laboratory of Cell Biology and Retrovirus, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | - Matias Moragas
- Laboratory of Cell Biology and Retrovirus, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | - Marcelo Dip
- Liver Transplant Service, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | - Esteban Halac
- Liver Transplant Service, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | - Paulo Cáceres Guido
- Unit of Clinical Pharmacokinetics, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | - Nieves Licciardone
- Central Laboratory, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | - Andrea Mangano
- Laboratory of Cell Biology and Retrovirus, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Andrea Bosaleh
- Pathology Service, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
| | | | - Paula Schaiquevich
- Unit of Clinical Pharmacokinetics, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Oscar Imventarza
- Liver Transplant Service, Hospital de Pediatría Juan P. Garrahan, Buenos Aires, Argentina
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30
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Tian JX, Zhang P, Miao WJ, Wang XD, Liu XO, Liao YX, Li S, Yan HH. Tacrolimus Levels in the Prophylaxis of Acute Graft-Versus-Host Disease in the Chinese Early After Hematopoietic Stem Cell Transplantation. Ther Drug Monit 2019; 41:620-627. [PMID: 31268965 DOI: 10.1097/ftd.0000000000000645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Tacrolimus has been widely accepted as the backbone of acute graft-versus-host disease (aGVHD) prophylaxis in allogeneic hematopoietic stem cell transplantation (alloHSCT). The present work evaluated whether tacrolimus concentrations early after transplant correlate with the incidence of aGVHD in Chinese alloHSCT recipients. METHODS One hundred four Chinese alloHSCT recipients were included in this retrospective study. All patients received standard prophylaxis with tacrolimus and short-term methotrexate. Blood samples were taken at steady-state for those on i.v. tacrolimus (Cv) or predose (C0) and 2 hours after the last oral dose (C2). RESULTS In the first 8 weeks after alloHSCT, significant variability in Cv, C0, and C2 of Chinese patients was observed. It was found that higher tacrolimus C0 and C2 values tended to be associated with a reduced risk of aGVHD, although this was a nonsignificant trend due to the small sample size involved. Receiver operating characteristic curve analysis indicated that Cv levels of ≥16.52 ng/mL, C0 levels of ≥5.56 ng/mL, and C2 levels of ≥7.83 ng/mL minimized the incidence of treatment failure during weeks 3-4 with intravenous administration and weeks 5-6 with oral administration. There was no statistically significant association of the patient liver and kidney function with the blood concentration of tacrolimus in the desired range of 5-20 ng/mL. CONCLUSIONS Tacrolimus therapeutic drug monitoring improved treatment outcomes of Chinese alloHSCT recipients. Cv measurements during weeks 3-4 and C0 or C2 measurements during weeks 5-6 better predicted aGVHD (I-IV) than the concentrations measured at other time points during the first 6 weeks after alloHSCT.
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Affiliation(s)
- Ji-Xin Tian
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Ping Zhang
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Wen-Juan Miao
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Xiao-Dan Wang
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Xue-Ou Liu
- Organization for Drug Clinical Trial, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Ying-Xi Liao
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Shan Li
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
| | - Hai-Hong Yan
- Department of Pharmacy, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Tianjin, People's Republic of China
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31
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Liu L, Ding Y, Jiao Z, Wu M, Li C, Liu J, Liu C, Hu Y, Li Q, Zhang H. Clinical Evaluation of the Tolerability, Pharmacokinetics, and Inhibition of Platelet Aggregation of Eptifibatide in Healthy Chinese Subjects. Clin Pharmacol Drug Dev 2019; 9:267-276. [PMID: 31197974 DOI: 10.1002/cpdd.717] [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: 03/21/2019] [Accepted: 05/22/2019] [Indexed: 11/11/2022]
Abstract
The present study aimed to evaluate the pharmacokinetic properties and antiplatelet aggregation activity of eptifibatide in healthy Chinese subjects. Eptifibatide (180 μg/kg) was administrated by 2 bolus injections 10 minutes apart, followed by a 2.0 μg/kg/min infusion for 24 hours. The eptifibatide pharmacokinetic and antiplatelet aggregation activities were evaluated using nonlinear mixed-effects modeling and noncompartmental analysis. Safety assessments included adverse events, hematology, and biochemistry tests. Twelve Chinese healthy subjects were enrolled and completed the study. Steady-state concentrations were achieved at 0.5 to 24 hours after dosing. The median time to maximum concentration was 13 minutes, and the mean terminal elimination half-life was 148.19 minutes. The effective inhibition of platelet aggregation (<20% platelet aggregation) occurred by 3 minutes after starting dosing to 4 hours after termination of the infusion. Eptifibatide concentrations were fitted with a 3-compartment model, and the typical value of clearance was 0.11 L/min, with no significant covariates found. Three mild adverse events were detected in the study. Eptifibatide displays high sensitivity and excellent tolerability in healthy Chinese subjects. The dosage of eptifibatide recommended on the label for whites can effectively inhibit platelet aggregation.
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Affiliation(s)
- Li Liu
- Department of Pediatrics, The First Hospital of Jilin University, Jilin, China
| | - Yanhua Ding
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Zheng Jiao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Min Wu
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Cuiyun Li
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Jingrui Liu
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Chengjiao Liu
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Yue Hu
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
| | - Qingmei Li
- Department of Pediatrics, The First Hospital of Jilin University, Jilin, China
| | - Hong Zhang
- Phase I Clinical Research Center, The First Hospital of Jilin University, Jilin, China
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32
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Riff C, Debord J, Monchaud C, Marquet P, Woillard JB. Population pharmacokinetic model and Bayesian estimator for 2 tacrolimus formulations in adult liver transplant patients. Br J Clin Pharmacol 2019; 85:1740-1750. [PMID: 30973981 DOI: 10.1111/bcp.13960] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 03/26/2019] [Accepted: 04/08/2019] [Indexed: 12/01/2022] Open
Affiliation(s)
- Camille Riff
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France
| | - Jean Debord
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France.,IPPRITT, Univ. Limoges, Limoges, France.,IPPRITT, U1248, INSERM, Limoges, France
| | - Caroline Monchaud
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France.,IPPRITT, Univ. Limoges, Limoges, France.,IPPRITT, U1248, INSERM, Limoges, France
| | - Pierre Marquet
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France.,IPPRITT, Univ. Limoges, Limoges, France.,IPPRITT, U1248, INSERM, Limoges, France
| | - Jean-Baptiste Woillard
- Department of Pharmacology and Toxicology, CHU Limoges, Limoges, France.,IPPRITT, Univ. Limoges, Limoges, France.,IPPRITT, U1248, INSERM, Limoges, France
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33
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Therapeutic Drug Monitoring of Tacrolimus-Personalized Therapy: Second Consensus Report. Ther Drug Monit 2019; 41:261-307. [DOI: 10.1097/ftd.0000000000000640] [Citation(s) in RCA: 227] [Impact Index Per Article: 45.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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34
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Brunet M, van Gelder T, Åsberg A, Haufroid V, Hesselink DA, Langman L, Lemaitre F, Marquet P, Seger C, Shipkova M, Vinks A, Wallemacq P, Wieland E, Woillard JB, Barten MJ, Budde K, Colom H, Dieterlen MT, Elens L, Johnson-Davis KL, Kunicki PK, MacPhee I, Masuda S, Mathew BS, Millán O, Mizuno T, Moes DJAR, Monchaud C, Noceti O, Pawinski T, Picard N, van Schaik R, Sommerer C, Vethe NT, de Winter B, Christians U, Bergan S. Therapeutic Drug Monitoring of Tacrolimus-Personalized Therapy: Second Consensus Report. Ther Drug Monit 2019. [DOI: 10.1097/ftd.0000000000000640
expr 845143713 + 809233716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
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