Effect of CYP3A4 Inhibitors and Inducers on Pharmacokinetics and Pharmacodynamics of Saxagliptin and Active Metabolite M2 in Humans Using Physiological-Based Pharmacokinetic Combined DPP-4 Occupancy

Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict CYP3A-Mediated Drug Interaction between Saxagliptin and Nicardipine: Bridging Rat-to-Human Extrapolation

The aim of this study was to predict the cytochrome P450 3A (CYP3A)-mediated drug-drug interactions (DDIs) between saxagliptin and nicardipine using a physiologically based pharmacokinetic (PBPK) model. Initially, in silico and in vitro parameters were gathered from experiments or the literature to construct PBPK models for each drug in rats. These models were integrated to predict the DDIs between saxagliptin, metabolized via CYP3A2, and nicardipine, exhibiting CYP3A inhibitory activity. The rat DDI PBPK model was completed by optimizing parameters using experimental rat plasma concentrations after co-administration of both drugs. Following co-administration in Sprague-Dawley rats, saxagliptin plasma concentration significantly increased, resulting in a 2.60-fold rise in AUC, accurately predicted by the rat PBPK model. Subsequently, the workflow of the rat PBPK model was applied to humans, creating a model capable of predicting DDIs between the two drugs in humans. Simulation from the human PBPK model indicated that nicardipine co-administration in humans resulted in a nearly unchanged AUC of saxagliptin, with an approximate 1.05-fold change, indicating no clinically significant changes and revealing a lack of direct translation of animal interaction results to humans. The animal-to-human PBPK model extrapolation used in this study could enhance the reliability of predicting drug interactions in clinical settings where DDI studies are challenging.

Prediction of drug-drug interactions between roflumilast and CYP3A4/1A2 perpetrators using a physiologically-based pharmacokinetic (PBPK) approach

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict changes in the pharmacokinetics (PK) and pharmacodynamics (PD, PDE4 inhibition) of roflumilast (ROF) and ROF N-oxide when co-administered with eight CYP3A4/1A2 perpetrators. The population PBPK model of ROF and ROF N-oxide has been successfully developed and validated based on the four clinical PK studies and five clinical drug-drug interactions (DDIs) studies. In PK simulations, every ratio of prediction to observation for PK parameters fell within the range 0.7 to 1.5. In DDI simulations, except for tow peak concentration ratios (Cmax) of ROF with rifampicin (prediction: 0.63 vs. observation: 0.19) and with cimetidine (prediction: 1.07 vs. observation: 1.85), the remaining predicted ratios closely matched the observed ratios. Additionally, the PBPK model suggested that co-administration with the three perpetrators (cimetidine, enoxacin, and fluconazole) may use with caution, with CYP3A4 strong inhibitor (ketoconazole and itraconazole) or with dual CYP3A41A2 inhibitor (fluvoxamine) may reduce to half-dosage or use with caution, while co-administration with CYP3A4 strong or moderate inducer (rifampicin, efavirenz) should avoid. Overall, the present PBPK model can provide recommendations for adjusting dosing regimens in the presence of DDIs.

Toxicity Derived from Interaction between Natural Compounds and Cancer Therapeutic Drugs Metabolized by CYP3A4: Lessons Learned from Two Clinical Case Reports

The use of natural compounds and, in general, the use of Complementary and Alternative Medicine (CAM), is growing steadily worldwide, both due to commercial pressure and the increasing use of self-medication and the desire to manage one's own personal health and well-being. Patients facing a cancer diagnosis are also strongly pressured to use these compounds, which are often added to standard therapeutic regimens, that should instead be based solely on diagnostic and therapeutic care pathways (DTCP) or evidence-based medicine (EBM). This study presents two clinical cases of cancer patients who presented to the pharmaceutical consultation service (PCD-Pharmacy Clinical Desk) established at the CRO Institute in Aviano, Italy. Both patients were using natural products along with prescribed chemotherapy. In the first case, a 55-year-old woman diagnosed with bilateral breast cancer with bone metastases, who was using natural compounds based on diosmin, escin (or aescin) and resveratrol in combination with ribociclib anticancer therapy, a severe ADR (neutropenia) was identified as a consequence of the drug-natural product interaction. In the second case, following a detailed medication review by the PCD, we avoided taking a therapeutic treatment (with natural compounds) that in itself could potentially render chemotherapy ineffective in a 57-year-old woman with multiple infiltrating ductal carcinoma of the left breast; the patient was planning to take a natural product containing St. John's Wort tincture and lemon balm tincture, in combination with paclitaxel and trastuzumab. In addition, we describe the corrective actions taken, thus outlining the main objectives of the activity of the PCD's pharmacy counseling service: first, to identify, report, and manage adverse drug reactions (ADRs), and second, to identify therapeutic combinations that present potential risks of toxicity or ineffectiveness of the drug therapy itself.

Physiologically-based pharmacokinetic modeling for optimal dosage prediction of olaparib when co-administered with CYP3A4 modulators and in patients with hepatic/renal impairment

This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict the maximum plasma concentration (Cmax) and trough concentration (Ctrough) at steady-state of olaparib (OLA) in Caucasian, Japanese and Chinese. Furthermore, the PBPK model was combined with mean and 95% confidence interval to predict optimal dosing regimens of OLA when co-administered with CYP3A4 modulators and administered to patients with hepatic/renal impairment. The dosing regimens were determined based on safety and efficacy PK threshold Cmax (< 12,500 ng/mL) and Ctrough (772-2500 ng/mL). The population PBPK model for OLA was successfully developed and validated, demonstrating good consistency with clinically observed data. The ratios of predicted to observed values for Cmax and Ctrough fell within the range of 0.5 to 2.0. When OLA was co-administered with a strong or moderate CYP3A4 inhibitor, the recommended dosing regimens should be reduced to 100 mg BID and 150 mg BID, respectively. Additionally, the PBPK model also suggested that OLA could be not recommended with a strong or moderate CYP3A4 inducer. For patients with moderate hepatic and renal impairment, the dosing regimens of OLA were recommended to be reduced to 200 mg BID and 150 mg BID, respectively. In cases of severe hepatic and renal impairment, the PBPK model suggested a dosing regimen of 100 mg BID for OLA. Overall, this present PBPK model can determine the optimal dosing regimens for various clinical scenarios involving OLA.

In-depth analysis of patterns in selection of different physiologically-based pharmacokinetic modeling tools: Part II - Assessment of model reusability and comparison between open and non-open source-code software

Whilst the reproducibility of models in the area of systems biology and quantitative systems pharmacology has been the focus of attention lately, the concept of 'reusability' is not addressed. With the advent of the 'Model Master File' dominating some regulatory discussions on pharmaceutical applications of physiologically-based pharmacokinetic (PBPK) models, reusability becomes a vital aspect of confidence in their use. Herein, we define 'reusability' specifically in the context of PBPK models and investigate the influence of open versus non-open source-code (NOSC) nature of the software on the extent of 'reusability'. Original articles (n = 145) that were associated with the development of novel PBPK models were identified as source models and citations to these reports, which involved further PBPK model development, were explored (n > 1800) for reuse cases of the source PBPK model whether in full or partial form. The nature of source-code was a major determinant of external reusability for PBPK models (>50% of the NOSC models as opposed <25% of open source-code [OSC]). Full reusability of the models was not common and mostly involved internal reuse of the OSC model (by the group who had previously developed the original model). The results were stratified by the software utilised (various), organisations involved (academia, industry, regulatory), and type of reusability (full vs. partial). The clear link between external reuse of models and NOSC PBPK software might stem from many elements related to quality and trust that require further investigation, and challenges the unfounded notion that OSC models are associated with higher uptake for reuse.

Prediction for Plasma Trough Concentration and Optimal Dosing of Imatinib under Multiple Clinical Situations Using Physiologically Based Pharmacokinetic Modeling

(1) Purpose: This study aimed to develop a physiologically based pharmacokinetic (PBPK) model to predict the trough concentration (C _trough) of imatinib (IMA) at steady state in patients and to explore the role of free concentration (f _up), α1-acid glycoprotein (AGP) level, and organic cation transporter 1 (OCT1) activity/expression in clinical efficacy. (2) Methods: The population PBPK model was built using physicochemical and biochemical properties, metabolizing and transporting kinetics, tissue distribution, and human physiological parameters. (3) Results: The PBPK model successfully predicted the C _trough of IMA administered alone in chronic phase (CP) and accelerated phase (AP) patients, the C _trough of IMA co-administered with six modulators, and C _trough in CP patients with hepatic impairment. Most of the ratios between predicted and observed data are within 0.70-1.30. Additionally, the recommendations for dosing adjustments for IMA have been given under multiple clinical uses. The sensitivity analysis showed that exploring the f _up and AGP level had a significant influence on the plasma C _trough of IMA. Meanwhile, the simulations also revealed that OCT1 activity and expression had a significant impact on the intracellular C _trough of IMA. (4) Conclusion: The current PBPK model can accurately predict the IMA C _trough and provide appropriate dosing adjustment recommendations in a variety of clinical situations.

Using a Mathematical Modeling To Simulate Pharmacokinetics and Urinary Glucose Excretion of Luseogliflozin and Explore the Role of SGLT1/2 in Renal Glucose Reabsorption

(1) Purpose: To develop a mathematical model combining physiologically based pharmacokinetic and urinary glucose excretion (PBPK-UGE) to simultaneously predict pharmacokinetic (PK) and UGE changes of luseogliflozin (LUS) as well as to explore the role of sodium-glucose cotransporters (SGLT1 and SGLT2) in renal glucose reabsorption (RGR) in humans. (2) Methods: The PBPK-UGE model was built using physicochemical and biochemical properties, binding kinetics data, affinity to SGLTs for glucose, and physiological parameters of renal tubules. (3) Results: The simulations using this model clarified that SGLT1/2 contributed 15 and 85%, respectively, to RGR in the absence of LUS. However, in the presence of LUS, the contribution proportion of SGLT1 rose to 52-76% in healthy individuals and 55-83% in T2DM patients, and that of SGLT2 reduced to 24-48 and 17-45%, respectively. Furthermore, this model supported the underlying mechanism that only 23-40% inhibition of the total RGR with 5 mg of LUS is resulted from SGLT1's compensatory effect and the reabsorption activity of unbound SGLT2. (4) Conclusion: This PBPK-UGE model can predict PK and UGE in healthy individuals and T2DM patients and can also analyze the contribution of SGLT1/2 to RGR with and without LUS.

Prediction for optimal dosage of pazopanib under various clinical situations using physiologically based pharmacokinetic modeling

This study aimed to apply a physiologically based pharmacokinetic (PBPK) model to predict optimal dosing regimens of pazopanib (PAZ) for safe and effective administration when co-administered with CYP3A4 inhibitors, acid-reducing agents, food, and administered in patients with hepatic impairment. Here, we have successfully developed the population PBPK model and the predicted PK variables by this model matched well with the clinically observed data. Most ratios of prediction to observation were between 0.5 and 2.0. Suitable dosage modifications of PAZ have been identified using the PBPK simulations in various situations, i.e., 200 mg once daily (OD) or 100 mg twice daily (BID) when co-administered with the two CYP3A4 inhibitors, 200 mg BID when simultaneously administered with food or 800 mg OD when avoiding food uptake simultaneously. Additionally, the PBPK model also suggested that dosing does not need to be adjusted when co-administered with esomeprazole and administration in patients with wild hepatic impairment. Furthermore, the PBPK model also suggested that PAZ is not recommended to be administered in patients with severe hepatic impairment. In summary, the present PBPK model can determine the optimal dosing adjustment recommendations in multiple clinical uses, which cannot be achieved by only focusing on AUC linear change of PK.

Diminazene Aceturate Reduces Angiotensin II Constriction and Interacts with the Spike Protein of Severe Acute Respiratory Syndrome Coronavirus 2

Diminazene aceturate (DIZE) is a putative angiotensin-converting enzyme 2 (ACE2) activator and angiotensin type 1 receptor antagonist (AT₁R). Its simple chemical structure possesses a negatively charged triazene segment that is homologous to the tetrazole of angiotensin receptor blockers (ARB), which explains its AT₁R antagonistic activity. Additionally, the activation of ACE2 by DIZE converts the toxic octapeptide angiotensin II (AngII) to the heptapeptides angiotensin 1–7 and alamandine, which promote vasodilation and maintains homeostatic balance. Due to DIZE’s protective cardiovascular and pulmonary effects and its ability to target ACE2 (the predominant receptor utilized by severe acute respiratory syndrome coronavirus 2 to enter host cells), it is a promising treatment for coronavirus 2019 (COVID-19). To determine DIZE’s ability to inhibit AngII constriction, in vitro isometric tension analysis was conducted on rabbit iliac arteries incubated with DIZE or candesartan and constricted with cumulative doses of AngII. In silico docking and ligand interaction studies were performed to investigate potential interactions between DIZE and other ARBs with AT₁R and the spike protein/ACE2 complex. DIZE, similar to the other ARBs investigated, was able to abolish vasoconstriction in response to AngII and exhibited a binding affinity for the spike protein/ACE2 complex (PDB 6LZ6). These results support the potential of DIZE as a treatment for COVID-19.

Physiologically based pharmacokinetic combined BTK occupancy modeling for optimal dosing regimen prediction of acalabrutinib in patients alone, with different CYP3A4 variants, co-administered with CYP3A4 modulators and with hepatic impairment

PURPOSE

To develop a mathematical model combined between physiologically based pharmacokinetic and BTK occupancy (PBPK-BO) to simultaneously predict pharmacokinetic (PK) and pharmacodynamic (PD) changes of acalabrutinib (ACA) and active metabolite ACP-5862 in healthy humans as well as PD in patients. Next, to use the PBPK-BO to determine the optimal dosing regimens in patients alone, with different CYP3A4 variants, when co-administration with four CYP3A4 modulators and in patients with hepatic impairment, respectively.

METHODS

The PBPK-BO model was built using physicochemical and biochemical properties of ACA and ACP-5862 and then verified by observed PK and PD data from healthy humans and patients. Finally, the model was applied to determine optimal dosing regimens in various clinical situations.

RESULTS

The simulations demonstrated that 100 mg ACA twice daily (BID) was the optimal dosing regimen in patients alone. Additionally, dosage regimens might be reduced to 50 mg BID in patients with five CYP3A4 variants. Moreover, the dosing regimen should be modified to 100 mg (even to 50 mg) once daily (QD) when co-administration with erythromycin or clarithromycin, and be increased to 200 mg BID with rifampicin, and but be avoided co-administration with itraconazole. Furthermore, dosage regimen simulations showed that optimal dosing might be decreased to 50 mg BID in patients with mild and moderate hepatic impairment, and be avoided taking ACA in severely hepatically impaired patients.

CONCLUSION

This PBPK-BO model can predict PK and PD in healthy humans and patients and also predict the optimal dosing regimens in various clinical situations.