Background Obese individuals are often underrepresented in clinical trials, leading to a lack of dosing guidance. Objective This study aimed to investigate which physiological parameters and drug properties determine drug disposition changes in obese using our physiologically based pharmacokinetic (PBPK) framework, informed with obese population characteristics. Methods Simulations were performed for ten drugs with clinical data in obese (i.e., midazolam, triazolam, caffeine, chlorzoxazone, acetaminophen, lorazepam, propranolol, amikacin, tobramycin, and glimepiride). PBPK drug models were developed and verified first against clinical data in non-obese (body mass index (BMI) ≤ 30 kg/m 2 ) and subsequently in obese (BMI ≥ 30 kg/m 2 ) without changing any drug parameters. Additionally, the PBPK model was used to study the effect of obesity on the pharmacokinetic parameters by simulating drug disposition across BMI, starting from 20 up to 60 kg/m 2 . Results Predicted pharmacokinetic parameters were within 1.25-fold (71.5%), 1.5-fold (21.5%) and twofold (7%) of clinical data. On average, clearance increased by 1.6% per BMI unit up to 64% for a BMI of 60 kg/m 2 , which was explained by the increased hepatic and renal blood flows. Volume of distribution increased for all drugs up to threefold for a BMI of 60 kg/m 2 ; this change was driven by pK a for ionized drugs and logP for neutral and unionized drugs. C max decreased similarly across all drugs while t max remained unchanged. Conclusion Both physiological changes and drug properties impact drug pharmacokinetics in obese subjects. Clearance increases due to enhanced hepatic and renal blood flows. Volume of distribution is higher for all drugs, with differences among drugs depending on their pK a /logP. Extended author information available on the last page of the article Key PointsDrug pharmacokinetics in obese subjects (BMI ≥ 30 kg/m 2 ) were accurately predicted by our physiologically based pharmacokinetic framework informed with our previously developed obese population repository (i.e., 71.5% of predictions were within the 1.25-fold and none outside the twofold of clinical data).The model predicted an average 1.6% increase in clearance per BMI unit, which was explained by an increase in hepatic and renal blood flows. The volume of distribution increased on average up to threefold for a BMI of 60 kg/m 2 ; this change was driven by drug properties (pK a and logP). Dosing in obese subjects needs to take into account both physiological parameters and drug properties.

Background Obesity is associated with physiological changes that can affect drug pharmacokinetics. Obese individuals are underrepresented in clinical trials, leading to a lack of evidence-based dosing recommendations for many drugs. Physiologically based pharmacokinetic (PBPK) modelling can overcome this limitation but necessitates a detailed description of the population characteristics under investigation. Objective The purpose of this study was to develop and verify a repository of the current anatomical, physiological, and biological data of obese individuals, including population variability, to inform a PBPK framework. Methods A systematic literature search was performed to collate anatomical, physiological, and biological parameters for obese individuals. Multiple regression analyses were used to derive mathematical equations describing the continuous effect of body mass index (BMI) within the range 18.5–60 kg/m 2 on system parameters. Results In total, 209 studies were included in the database. The literature reported mostly BMI-related changes in organ weight, whereas data on blood flow and biological parameters (i.e. enzyme abundance) were sparse, and hence physiologically plausible assumptions were made when needed. The developed obese population was implemented in Matlab ® and the predicted system parameters obtained from 1000 virtual individuals were in agreement with observed data from an independent validation obese population. Our analysis indicates that a threefold increase in BMI, from 20 to 60 kg/m 2 , leads to an increase in cardiac output (50%), liver weight (100%), kidney weight (60%), both the kidney and liver absolute blood flows (50%), and in total adipose blood flow (160%). Conclusion The developed repository provides an updated description of a population with a BMI from 18.5 to 60 kg/m 2 using continuous physiological changes and their variability for each system parameter. It is a tool that can be implemented in PBPK models to simulate drug pharmacokinetics in obese individuals.

Background Long-acting (LA) intramuscular cabotegravir and rilpivirine are prone to drug-drug interactions (DDI). However, given the long dosing interval, the conduct of clinical DDIs studies with LA antiretrovirals is challenging. We performed virtual clinical DDI studies using physiologically based pharmacokinetic (PBPK) modelling to provide recommendations for the management of DDIs with strong or moderate inducers such as rifampicin or rifabutin. Methods Each DDI scenario included a cohort of virtual individuals (50% female) between 20-50 years of age with a body mass index of 18-30 kg/m2. Cabotegravir and rilpivirine were given alone and in combination with rifampicin or rifabutin. The predictive performance of the PBPK model to simulate cabotegravir and rilpivirine pharmacokinetics after oral and intramuscular administration and to reproduce DDIs with rifampicin and rifabutin was first verified against available observed clinical data. The verified model was subsequently used to simulate unstudied DDI scenarios. Results At steady-state, the strong inducer rifampicin was predicted to decrease the area under the curve (AUC) of LA cabotegravir by 61% and rilpivirine by 38%. An increase in the dosing frequency did not overcome the DDI with rifampicin. The moderate inducer rifabutin was predicted to reduce the AUC of LA cabotegravir by 16% and rilpivirine by 18%. The DDI with rifabutin can be overcome by administering LA cabotegravir/rilpivirine monthly together with a daily oral rilpivirine dose of 25 mg. Conclusion LA cabotegravir/rilpivirine should be avoided with strong inducers but coadministration with moderate inducers is possible by adding oral rilpivirine daily dosing to the monthly injection.