Adam S. Darwich

Why has model-informed precision dosing not yet become common clinical reality?: Lessons from the past and a roadmap for the future

Patient groups prone to polypharmacy and special subpopulations are susceptible to suboptimal treatment. Refined dosing in special populations is imperative to improve therapeutic response and/or lowering the risk of toxicity. Model‐informed precision dosing (MIPD) may improve treatment outcomes by achieving the optimal dose for an individual patient. There is, however, relatively little published evidence of large‐scale utility and impact of MIPD, where it is often implemented as local collaborative efforts between academia and healthcare. This article highlights some successful applications of bringing MIPD to clinical care and proposes strategies for wider integration in healthcare. Considerations are brought up herein that will need addressing to see MIPD become “widespread clinical practice,” among those, wider interdisciplinary collaborations and the necessity for further evidence‐based efficacy and cost–benefit analysis of MIPD in healthcare. The implications of MIPD on regulatory policies and pharmaceutical development are also discussed as part of the roadmap.

A mechanistic pharmacokinetic model to assess modified oral drug bioavailability post bariatric surgery in morbidly obese patients: Interplay between CYP3A gut wall metabolism, permeability and dissolution

Objectives  Due to the multi‐factorial physiological implications of bariatric surgery, attempts to explain trends in oral bioavailability following bariatric surgery using singular attributes of drugs or simplified categorisations such as the biopharmaceutics classification system have been unsuccessful. So we have attempted to use mechanistic models to assess changes to bioavailability of model drugs.

Physiologically-Based Pharmacokinetics

External control of tissues and cells, by hormones, nerves, and other stimuli, involves the transduction of signals from ligand-activated receptors to control of rate-limiting enzymes or proteins that affect key steps in metabolism, gene transcription or other processes within the cells. The signal transduction is carried out by a network of interacting signal mediators, i.e. proteins and small molecule transducers. Such signaling transduction networks display a high degree of complexity, which is due to the presence of feed-forward and feedback loops, both negative and positive, and to the fact that interactions change over time and according to intracellular location. In combination with multiple layers of control, redundancy, shared signal mediators, shared signal paths, and cross-talk between signals, this leads to a complexity that poses new challenges to progress in dissecting and understanding cellular control. Furthermore, many diseases, such as cancer, insulin resistance, and type 2 diabetes, are associated with malfunctioning in the complex signaling networks.

Evaluation of an In Silico PBPK Post-Bariatric Surgery Model through Simulating Oral Drug Bioavailability of Atorvastatin and Cyclosporine.

An increasing prevalence of morbid obesity has led to dramatic increases in the number of bariatric surgeries performed. Altered gastrointestinal physiology following surgery can be associated with modified oral drug bioavailability (Foral). In the absence of clinical data, an indication of changes to Foral via systems pharmacology models would be of value in adjusting dose levels after surgery. A previously developed virtual “post‐bariatric surgery” population was evaluated through mimicking clinical investigations on cyclosporine and atorvastatin after bariatric surgery. Cyclosporine simulations displayed a reduced fraction absorbed through gut wall (fa) and Foral after surgery, consistent with reported observations. Simulated atorvastatin Foral postsurgery was broadly reflective of observed data with indications of counteracting interplay between reduced fa and an increased fraction escaping gut wall metabolism (FG). Inability to fully recover observed atorvastatin exposure after biliopancreatic diversion with duodenal switch highlights the current gap regarding the knowledge of associated biological changes.

Meta-analysis of the turnover of intestinal epithelia in preclinical animal species and humans.

Due to the rapid turnover of the small intestinal epithelia, the rate at which enterocyte renewal occurs plays an important role in determining the level of drug-metabolizing enzymes in the gut wall. Current physiologically based pharmacokinetic (PBPK) models consider enzyme and enterocyte recovery as a lumped first-order rate. An assessment of enterocyte turnover would enable enzyme and enterocyte renewal to be modeled more mechanistically. A literature review together with statistical analysis was employed to establish enterocyte turnover in human and preclinical species. A total of 85 studies was identified reporting enterocyte turnover in 1602 subjects in six species. In mice, the geometric weighted combined mean (WX) enterocyte turnover was 2.81 ± 1.14 days (n = 169). In rats, the weighted arithmetic mean enterocyte turnover was determined to be 2.37 days (n = 501). Humans exhibited a geometric WX enterocyte turnover of 3.48 ± 1.55 days for the gastrointestinal epithelia (n = 265), displaying comparable turnover to that of cytochrome P450 enzymes in vitro (0.96–4.33 days). Statistical analysis indicated humans to display longer enterocyte turnover as compared with preclinical species. Extracted data were too sparse to support regional differences in small intestinal enterocyte turnover in humans despite being indicated in mice. The utilization of enterocyte turnover data, together with in vitro enzyme turnover in PBPK modeling, may improve the predictions of metabolic drug-drug interactions dependent on enzyme turnover (e.g., mechanism-based inhibition and enzyme induction) as well as absorption of nanoparticle delivery systems and intestinal metabolism in special populations exhibiting altered enterocyte turnover.

Analysis of the impact of controlled release formulations on oral drug absorption, gut wall metabolism and relative bioavailability of CYP3A substrates using a physiologically-based pharmacokinetic model.

Controlled release (CR) formulations are usually designed to achieve similar exposure (AUC) levels as the marketed immediate release (IR) formulation. However, the AUC is often lower following CR compared to IR formulations. There are a few exceptions when the CR formulations have shown higher AUC. This study investigated the impact of CR formulations on oral drug absorption and CYP3A4-mediated gut wall metabolism. A review of the current literature on relative bioavailability (Frel) between CR and IR formulations of CYP3A substrates was conducted. This was followed by a systematic analysis to assess the impact of the release characteristics and the drug-specific factors (including metabolism and permeability) on oral bioavailability employing a physiologically-based pharmacokinetic (PBPK) modelling and simulation approach. From the literature review, only three CYP3A4 substrates showed higher Frel when formulated as CR. Several scenarios were investigated using the PBPK approach; in most of them, the oral absorption of CR formulations was lower as compared to the IR formulations. However, for highly permeable compounds that were CYP3A4 substrates the reduction in absorption was compensated by an increase in the fraction that escapes from first pass metabolism in the gut wall (FG), where the magnitude was dependent on CYP3A4 affinity. The systematic simulations of various interplays between different parameters demonstrated that BCS class 1 highly-cleared CYP3A4 substrates can display up to 220% higher relative bioavailability when formulated as CR compared to IR, in agreement with the observed data collected from the literature. The results and methodology of this study can be employed during the formulation development process in order to optimize drug absorption, especially for CYP3A4 substrates.

Semiphysiologically based pharmacokinetic model for midazolam and CYP3A mediated metabolite 1‐OH‐midazolam in morbidly obese and weight loss surgery patients

This study aimed to describe the pharmacokinetics of midazolam and its cytochrome P450 3A (CYP3A) mediated metabolite 1‐OH‐midazolam in morbidly obese patients receiving oral and i.v. midazolam before (n = 20) and one year after weight loss surgery (n = 18), thereby providing insight into the influence of weight loss surgery on CYP3A activity in the gut wall and liver. In a semiphysiologically based pharmacokinetic (semi‐PBPK) model in which different blood flow scenarios were evaluated, intrinsic hepatic clearance of midazolam (CLint,H) was 2 (95% CI 1.40–1.64) times higher compared to morbidly obese patients before surgery (P < 0.01). Midazolam gut wall clearance (CLint,G) was slightly lower in patients after surgery (P > 0.05), with low values for both groups. The results of the semi‐PBPK model suggest that, in patients after weight loss surgery, CYP3A hepatic metabolizing capacity seems to recover compared to morbidly obese patients, whereas CYP3A mediated CLint,G was low for both populations and showed large interindividual variability.

IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 3: Identifying gaps in system parameters by analysing In Silico performance across different compound classes

&NA; Three Physiologically Based Pharmacokinetic software packages (GI‐Sim, Simcyp® Simulator, and GastroPlus™) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded “bottom‐up” anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (Foral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foral was also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. Foral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water‐soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug‐specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data “as is” in this blinded bottom‐up prediction approach. Graphical Abstract Figure. No caption available.

IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2 : An introduction to the simulation exercise and overview of results

&NA; Orally administered drugs are subject to a number of barriers impacting bioavailability (Foral), causing challenges during drug and formulation development. Physiologically‐based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI‐Sim, Simcyp®, and GastroPlus™) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm‐institution‐software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two‐fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, Foral and relative AUC (Frel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large‐scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7‐fold differences in AFE between SimCYP and GI‐Sim, however average performance was relatively consistent across the three software platforms. Graphical abstract Figure. No caption available.

IMI – oral biopharmaceutics tools project – evaluation of bottom-up PBPK prediction success part 1: Characterisation of the OrBiTo database of compounds

&NA; Predicting oral bioavailability (Foral) is of importance for estimating systemic exposure of orally administered drugs. Physiologically‐based pharmacokinetic (PBPK) modelling and simulation have been applied extensively in biopharmaceutics recently. The Oral Biopharmaceutical Tools (OrBiTo) project (Innovative Medicines Initiative) aims to develop and improve upon biopharmaceutical tools, including PBPK absorption models. A large‐scale evaluation of PBPK models may be considered the first step. Here we characterise the OrBiTo active pharmaceutical ingredient (API) database for use in a large‐scale simulation study. The OrBiTo database comprised 83 APIs and 1475 study arms. The database displayed a median logP of 3.60 (2.40–4.58), human blood‐to‐plasma ratio of 0.62 (0.57–0.71), and fraction unbound in plasma of 0.05 (0.01–0.17). The database mainly consisted of basic compounds (48.19%) and Biopharmaceutics Classification System class II compounds (55.81%). Median human intravenous clearance was 16.9 L/h (interquartile range: 11.6–43.6 L/h; n = 23), volume of distribution was 80.8 L (54.5–239 L; n = 23). The majority of oral formulations were immediate release (IR: 87.6%). Human Foral displayed a median of 0.415 (0.203–0.724; n = 22) for IR formulations. The OrBiTo database was found to be largely representative of previously published datasets. 43 of the APIs were found to satisfy the minimum inclusion criteria for the simulation exercise, and many of these have significant gaps of other key parameters, which could potentially impact the interpretability of the simulation outcome. However, the OrBiTo simulation exercise represents a unique opportunity to perform a large‐scale evaluation of the PBPK approach to predicting oral biopharmaceutics. Graphical abstract Figure. No caption available.