Physiologically Based Pharmacokinetic Modeling of Fimasartan, Amlodipine, and Hydrochlorothiazide for the Investigation of Drug-Drug Interaction Potentials

Risk Assessment for Biopharmaceutics Classification System Class IV Molecule Containing Immediate Release Products: Use of In-Silico Prediction Tools and Physiologically Based Pharmacokinetic Modeling

Nitrosamines drug substance related impurities (NDSRI) are organic impurities, highly potent mutagenic substances that are classified as human carcinogens. Regulatory guidance's in this area provide procedures for control and risk mitigation of NDSRI's in drug products. While efforts are made to control the NDSRI's, cases where NDSRI's are observed post- pivotal bioequivalence studies may require additional bioequivalence studies, between pre- and post- change formulations. The recent USFDA (United State Food and Drug Administration) guidance on "Control of Nitrosamine Impurities in Human Drugs" provides alternative BE methodologies for biopharmaceutics classification system (BCS) I, II and III drugs based on in vitro testing. For BCS IV molecule containing immediate release (IR) formulations, physiologically based pharmacokinetic (PBPK) modeling approach is recommended. In this context, this present article discusses use of PBPK modeling approaches as alternative BE methodologies for BCS IV molecule containing IR products. We have summarized use of in-house in silico tool for early risk prediction of NDSRI's solely based on molecule structure. This tool was used to predict the carcinogenic potential of 37 BCS IV molecules and further clinical exposure risk assessment was conducted on identified 5 high risk category molecules namely edoxaban, selumetinib, bosutinib, furosemide, hydrochlorothiazide where transporters are involved in absorption. The PBPK models were used to evaluate the impact of altered permeability and transporter kinetics on exposures, that may happen in presence of antioxidants. Further, the impact of permeability within ± 10-20% was evaluated on clinical exposures to determine permeability safe space (region within which bioequivalence is guaranteed as compared to the target formulation).

Advancements in Virtual Bioequivalence: A Systematic Review of Computational Methods and Regulatory Perspectives in the Pharmaceutical Industry

BACKGROUND/OBJECTIVES

The rise of virtual bioequivalence studies has transformed the pharmaceutical landscape, enabling more efficient drug development processes. This systematic review aims to explore advancements in physiologically based pharmacokinetic (PBPK) modeling, its regulatory implications, and its role in achieving virtual bioequivalence, particularly for complex drug formulations.

METHODS

We conducted a systematic review of clinical trials using computational methods, particularly PBPK modeling, to carry out bioequivalence assessments. Eligibility criteria are emphasized during in silico modeling and pharmacokinetic simulations. Comprehensive literature searches were performed across databases such as PubMed, Scopus, and the Cochrane Library. A search strategy using key terms and Boolean operators ensured that extensive coverage was achieved. We adhered to the PRISMA guidelines in regard to the study selection, data extraction, and quality assessment, focusing on key characteristics, methodologies, outcomes, and regulatory perspectives from the FDA and EMA.

RESULTS

Our findings indicate that PBPK modeling significantly enhances the prediction of pharmacokinetic profiles, optimizing dosing regimens, while minimizing the need for extensive clinical trials. Regulatory agencies have recognized this utility, with the FDA and EMA developing frameworks to integrate in silico methods into drug evaluations. However, challenges such as study heterogeneity and publication bias may limit the generalizability of the results.

CONCLUSIONS

This review highlights the critical need for standardized protocols and robust regulatory guidelines to facilitate the integration of virtual bioequivalence methodologies into pharmaceutical practices. By embracing these advancements, the pharmaceutical industry can improve drug development efficiency and patient outcomes, paving the way for innovative therapeutic solutions. Continued research and adaptive regulatory frameworks will be essential in navigating this evolving field.

The Impact of Paediatric Obesity on Drug Pharmacokinetics: A Virtual Clinical Trials Case Study with Amlodipine

The incidence of paediatric obesity continues to rise worldwide and contributes to a range of diseases including cardiovascular disease. Obesity in children has been shown to impact upon the plasma concentrations of various compounds, including amlodipine. Nonetheless, information on the influence of obesity on amlodipine pharmacokinetics and the need for dose adjustment has not been studied previously. This study applied the physiologically based pharmacokinetic modelling and established a paediatric obesity population to assess the impact of obesity on amlodipine pharmacokinetics in children and explore the possible dose adjustments required to reach the same plasma concentration as non-obese paediatrics. The difference in predicted maximum concentration (Cmax) and area under the curve (AUC) were significant between children with and without obesity across the age group 2 to 18 years old when a fixed-dose regimen was used. On the contrary, a weight-based dose regimen showed no difference in Cmax between obese and non-obese from 2 to 9 years old. Thus, when a fixed-dose regimen is to be administered, a 1.25- to 1.5-fold increase in dose is required in obese children to achieve the same Cmax concentration as non-obese children, specifically for children aged 5 years and above.

Simultaneous Analysis of a Combination of Anti-Hypertensive Drugs, Fimasartan, Amlodipine, and Hydrochlorothiazide, in Rats Using LC-MS/MS and Subsequent Application to Pharmacokinetic Drug Interaction with Red Ginseng Extract

Fimasartan, amlodipine, and hydrochlorothiazide are commonly used in combination therapies as antihypertensive drugs. This study aimed to develop and validate an analytical method for fimasartan, its active and major metabolite fimasartan-amide, amlodipine, and hydrochlorothiazide in rat plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The standard calibration curves for fimasartan (1−500 ng/mL), its active and major metabolite fimasartan-amide (0.3−100 ng/mL), amlodipine (0.5−200 ng/mL), and hydrochlorothiazide (5−5000 ng/mL) were linear with R2 > 0.9964, and the inter- and intra-day accuracy and precision and stability were within the acceptable criteria. Using this validated analytical method, the pharmacokinetic interaction of these triple combination drugs between single administration and concomitant administration of the triple combination was investigated; the results did not reveal a significant difference in any of the pharmacokinetic parameters. Based on these results, we investigated the effects of red ginseng extract (RGE) on the pharmacokinetics of fimasartan, fimasartan-amide, amlodipine, and hydrochlorothiazide after oral administration of the combination in rats. No significant difference was observed in the pharmacokinetic parameters of fimasartan, fimasartan-amide, amlodipine, and hydrochlorothiazide, except for the Tmax values of amlodipine. The delayed Tmax value of amlodipine was attributed to its decreased intestinal permeability after repeated RGE treatments. In conclusion, using a combination of antihypertensive drugs and simultaneous analytical methods, we established efficient drug interaction and toxicokinetic studies using a small number of animals.

Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives

Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era in cardiovascular medicine, but their use somewhat lags behind that in other fields.

Evaluation for Potential Drug-Drug Interaction of MT921 Using In Vitro Studies and Physiologically-Based Pharmacokinetic Models

MT921 is a new injectable drug developed by Medytox Inc. to reduce submental fat. Cholic acid is the active pharmaceutical ingredient, a primary bile acid biosynthesized from cholesterol, endogenously produced by liver in humans and other mammals. Although individuals treated with MT921 could be administered with multiple medications, such as those for hypertension, diabetes, and hyperlipidemia, the pharmacokinetic drug–drug interaction (DDI) has not been investigated yet. Therefore, we studied in vitro against drug-metabolizing enzymes and transporters. Moreover, we predicted the potential DDI between MT921 and drugs for chronic diseases using physiologically-based pharmacokinetic (PBPK) modeling and simulation. The magnitude of DDI was found to be negligible in in vitro inhibition and induction of cytochrome P450s and UDP-glucuronosyltransferases. Organic anion transporting polypeptide (OATP)1B3, organic anion transporter (OAT)3, Na⁺-taurocholate cotransporting polypeptide (NTCP), and apical sodium-dependent bile acid transporter (ASBT) are mainly involved in MT921 transport. Based on the result of in vitro experiments, the PBPK model of MT921 was developed and evaluated by clinical data. Furthermore, the PBPK model of amlodipine was developed and evaluated. PBPK DDI simulation results indicated that the pharmacokinetics of MT921 was not affected by the perpetrator drugs. In conclusion, MT921 could be administered without a DDI risk based on in vitro study and related in silico simulation. Further clinical studies are needed to validate this finding.