Accelerating Clinical Development of Idasanutlin through a Physiologically Based Pharmacokinetic Modeling Risk Assessment for CYP450 Isoenzyme-Related Drug-Drug Interactions.

Idasanutlin is a potent inhibitor of the p53-MDM2 interaction that enables reactivation of the p53 pathway, which induces cell cycle arrest and/or apoptosis in tumor cells expressing functional p53. It was investigated for the treatment of solid tumors and several hematologic indications such as relapsed/refractory acute myeloid leukemia, polycythemia vera, or non-Hodgkin lymphoma. For safety reasons, it cannot be given in healthy volunteers for drug-drug interaction (DDI) explorations. This triggered the need for in silico explorations on top of the one available CYP3A clinical DDI study with posaconazole in solid tumor patients. Idasanutlin's clearance is dependent on CYP3A4/2C8 forming its major circulating metabolite M4, with contributions from UGT1A3 and biliary excretion. Idasanutlin and M4 have low permeability, very low clearance, and extremely low unbound fraction in plasma (<0.001), which makes in vitro data showing inhibition on CYP3A4/2C8 enzymes challenging to translate to clinical relevance. Physiologically-based pharmacokinetic models of idasanutlin and M4 have been established to simulate perpetrator and victim DDI scenarios and to evaluate whether further DDI studies in oncology patients are necessary. Modeling indicated that idasanutlin and M4 would show no or weak clinical inhibition of selective CYP3A4/2C8 substrates. Co-administered strong CYP3A and CYP2C8 inhibitors might lead to weak or moderate idasanutlin exposure increases, and the strong inducer rifampicin might cause moderate exposure reduction. As the simulated idasanutlin systemic exposure changes would be within the range of observed intrinsic variability, the target population can take co-medications that are either CYP2C8/3A4 inhibitors or weak/moderate CYP2C8/3A4 inducers without dose adjustment. SIGNIFICANCE STATEMENT: Clinical trials for idasanutlin are restricted to cancer patients, which imposes practical, scientific, and ethical challenges on drug-drug interaction investigations. Furthermore, idasanutlin and its major circulating metabolite have very challenging profiles of absorption, distribution, metabolism and excretion including high protein binding, low permeability and a combination of different elimination pathways each with extremely low clearance. Nonetheless, physiologically-based pharmacokinetic models could be established and applied for drug-drug interaction risk assessment and were especially useful to provide guidance on concomitant medications in patients.

Addressing Today's Absorption, Distribution, Metabolism, and Excretion (ADME) Challenges in the Translation of In Vitro ADME Characteristics to Humans: A Case Study of the SMN2 mRNA Splicing Modifier Risdiplam.

Small molecules that present complex absorption, distribution, metabolism, and elimination (ADME) properties can be challenging to investigate as potential therapeutics. Acquiring data through standard methods can yield results that are insufficient to describe the in vivo situation, which can affect downstream development decisions. Implementing in vitro-in vivo-in silico strategies throughout the drug development process is effective in identifying and mitigating risks while speeding up their development. Risdiplam (Evrysdi)-an orally bioavailable, small molecule approved by the US Food and Drug Administration and more recently by the European Medicines Agency for the treatment of patients ≥2 months of age with spinal muscular atrophy-is presented here as a case study. Risdiplam is a low-turnover compound whose metabolism is mediated through a non-cytochrome P450 enzymatic pathway. Four main challenges of risdiplam are discussed: predicting in vivo hepatic clearance, determining in vitro metabolites with regard to metabolites in safety testing guidelines, elucidating enzymes responsible for clearance, and estimating potential drug-drug interactions. A combination of in vitro and in vivo results was successfully extrapolated and used to develop a robust physiologically based pharmacokinetic model of risdiplam. These results were verified through early clinical studies, further strengthening the understanding of the ADME properties of risdiplam in humans. These approaches can be applied to other compounds with similar ADME profiles, which may be difficult to investigate using standard methods. SIGNIFICANCE STATEMENT: Risdiplam is the first approved, small-molecule, survival of motor neuron 2 mRNA splicing modifier for the treatment of spinal muscular atrophy. The approach taken to characterize the absorption, distribution, metabolism, and excretion (ADME) properties of risdiplam during clinical development incorporated in vitro-in vivo-in silico techniques, which may be applicable to other small molecules with challenging ADME. These strategies may be useful in improving the speed at which future drug molecules can be developed.

Development of a physiologically based pharmacokinetic model for mefloquine and its application alongside a clinical effectiveness model to select an optimal dose for prevention of malaria in young Caucasian children.

AIMS: To predict the optimal chemoprophylactic dose of mefloquine in infants of 5-10 kg using physiologically based pharmacokinetic (PBPK) and clinical effectiveness models. METHODS: The PBPK model was developed in Simcyp version 14.1 and verified against clinical pharmacokinetic data in adults; the final model, accounting for developmental physiology and enzyme ontogeny was then applied in the paediatric population. The clinical effectiveness model utilized real-world chemoprophylaxis data with stratification of output by age and including infant data from the UK population. RESULTS: PBPK simulations in infant populations depend on the assumed fraction of mefloquine metabolized by CYP3A4 (0.47, 0.95) and on the associated CYP3A4 ontogeny (Salem, Upreti). However, all scenarios suggest that a dose of 62.5 mg weekly achieves or exceeds the exposure in adults following a 250 mg weekly dose and results in a minimum plasma concentration of 620 ng ml-1 , which is considered necessary to achieve 95% prophylactic efficacy. The clinical effectiveness model predicts a 96% protective efficacy from mefloquine chemoprophylaxis at 62.5 mg weekly. CONCLUSIONS: The PBPK and clinical effectiveness models are mutually supportive and suggest a prophylactic dose of 62.5 mg weekly in the Caucasian 5-10 kg infant population travelling to endemic countries. This dual approach offers a novel route to dose selection in a vulnerable population, where clinical trials would be difficult to conduct.

A phase 1 healthy male volunteer single escalating dose study of the pharmacokinetics and pharmacodynamics of risdiplam (RG7916, RO7034067), a SMN2 splicing modifier.

AIMS: Risdiplam (RG7916, RO7034067) is an orally administered, centrally and peripherally distributed, survival of motor neuron 2 (SMN2) mRNA splicing modifier for the treatment of spinal muscular atrophy (SMA). The objectives of this entry-into-human study were to assess the safety, tolerability, pharmacokinetics (PK) and pharmacodynamics of risdiplam, and the effect of the strong CYP3A inhibitor itraconazole on the PK of risdiplam in healthy male volunteers. METHODS: Part 1 had a randomized, double-blind, adaptive design with 25 subjects receiving single ascending oral doses of risdiplam (ranging from 0.6-18.0 mg, n = 18) or placebo (n = 7). A Bayesian framework was applied to estimate risdiplam's effect on SMN2 mRNA. The effect of multiple doses of itraconazole on the PK of risdiplam was also assessed using a two-period cross-over design (n = 8). RESULTS: Risdiplam in the fasted or fed state was well tolerated. Risdiplam exhibited linear PK over the dose range with a multi-phasic decline with a mean terminal half-life of 40-69 h. Food had no relevant effect, and itraconazole had only a minor effect on plasma PK indicating a low fraction of risdiplam metabolized by CYP3A. The highest tested dose of 18.0 mg risdiplam led to approximately 41% (95% confidence interval 27-55%) of the estimated maximum increase in SMN2 mRNA. CONCLUSIONS: Risdiplam was well tolerated and proof of mechanism was demonstrated by the intended shift in SMN2 splicing towards full-length SMN2 mRNA. Based on these data, Phase 2/3 studies of risdiplam in patients with SMA are now ongoing.

Low Potential of Basimglurant to Be Involved in Drug-Drug Interactions: Influence of Non-Michaelis-Menten P450 Kinetics on Fraction Metabolized.

Basimglurant, a novel mGlu5-negative allosteric modulator under development for the treatment of major depressive disorder, is cleared via cytochrome P450 (P450)-mediated oxidative metabolism. Initial enzyme phenotyping studies indicated that CYP3A4/5 dominates basimglurant metabolism and highlights a risk for drug-drug interactions when it is comedicated with strong CYP3A4/5 inhibitors or inactivators; however, a clinical drug-drug interaction (DDI) study using the potent and selective CYP3A4/5 inhibitor ketoconazole resulted in an area under the curve (AUC) AUCi/AUC ratio of only 1.24. A further study using the CYP3A4 inducer carbamazepine resulted in an AUCi/AUC ratio of 0.69. More detailed in vitro enzyme phenotyping and kinetics studies showed that, at the low concentrations attained clinically, basimglurant metabolic clearance is catalyzed mainly by CYP1A2. The relative contributions of the enzymes were estimated as 70:30 CYP1A2:CYP3A4/5. Using this information, a clinical study using the CYP1A2 inhibitor fluvoxamine was performed, resulting in an AUCi/AUC ratio of 1.60, confirming the role of CYP1A2 and indicating a balanced DDI risk profile. Basimglurant metabolism kinetics show enzyme dependency: CYP1A2-mediated metabolism follows Michaelis-Menten kinetics, whereas CYP3A4 and CYP3A5 follow sigmoidal kinetics [with similar constant (KM) and S50 values]. The interplay of the different enzyme kinetics leads to changing fractional enzyme contributions to metabolism with substrate concentration, even though none of the metabolic enzymes is saturated. This example demonstrates the relevance of non-Michaelis-Menten P450 enzyme kinetics and highlights the need for a thorough understanding of metabolism enzymology to make accurate predictions for human metabolism in vivo.

Evaluating a physiologically based pharmacokinetic model for prediction of omeprazole clearance and assessing ethnic sensitivity in CYP2C19 metabolic pathway.

PURPOSE: The purpose of this study is to evaluate the ethnicity-specific population models in the SimCYP Simulator® for prediction of omeprazole clearance with attention to differences in the CYP2C19 metabolic pathway. METHODS: The SimCYP® models incorporating Caucasian, Chinese, and Japanese population-specific demographic, physiological, and enzyme data were applied to simulate omeprazole pharmacokinetics. Published pharmacokinetic data of omeprazole after intravenous or oral administration in Caucasian, Chinese, and Japanese were used for the evaluation. RESULTS: Following oral administration, the ratio of the predicted to observed geometric mean of omeprazole clearance in Caucasian extensive metabolizers (EMs) was 0.88. The ratios in Chinese EMs were 1.16 and 0.99 after intravenous and oral administration, respectively. The ratios in Japanese EMs were 0.88 and 0.71 after intravenous and oral administration, respectively. Significant differences (2-fold) in the observed oral clearance of omeprazole were identified between Caucasian and Asian (Chinese and Japanese) EMs while the observed oral and intravenous clearances of omeprazole were similar between Chinese and Japanese EMs. Physiologically based pharmacokinetics (PBPK) models within SimCYP accurately predicted the difference in the observed oral clearance between Caucasian and Chinese EMs but overpredicted the difference between Caucasians and Japanese EMs due to under-prediction of oral clearance in Japanese EMs. CONCLUSIONS: The PBPK model within SimCYP adequately predicted omeprazole clearance in Caucasian, Chinese, and Japanese EMs and the 2-fold differences in clearance of omeprazole between Caucasian and Asian EMs. This may lead to early identification of ethnic sensitivity in clearance and the need for different dosing regimens in a specific ethnic group for substrates of CYP2C19 which can support the rational design of bridging clinical trials.

Estimation of FMO3 Ontogeny by Mechanistic Population Pharmacokinetic Modelling of Risdiplam and Its Impact on Drug-Drug Interactions in Children.

BACKGROUND AND OBJECTIVE: Spinal muscular atrophy (SMA) is a progressive neuromuscular disease caused by insufficient levels of survival motor neuron (SMN) protein. Risdiplam (EvrysdiTM) increases SMN protein and is approved for the treatment of SMA. Risdiplam has high oral bioavailability and is primarily eliminated through hepatic metabolism by flavin-containing monooxygenase3 (FMO3) and cytochrome P450 (CYP) 3A, by 75% and 20%, respectively. While the FMO3 ontogeny is critical input data for the prediction of risdiplam pharmacokinetics (PK) in children, it was mostly studied in vitro, and robust in vivo FMO3 ontogeny is currently lacking. We derived in vivo FMO3 ontogeny by mechanistic population PK modelling of risdiplam and investigated its impact on drug-drug interactions in children. METHODS: Population and physiologically based PK (PPK and PBPK) modelling conducted during the development of risdiplam were integrated into a mechanistic PPK (Mech-PPK) model to estimate in vivo FMO3 ontogeny. A total of 10,205 risdiplam plasma concentration-time data from 525 subjects aged 2 months-61 years were included. Six different structural models were examined to describe the in vivo FMO3 ontogeny. Impact of the newly estimated FMO3 ontogeny on predictions of drug-drug interaction (DDI) in children was investigated by simulations for dual CYP3A-FMO3 substrates including risdiplam and theoretical substrates covering a range of metabolic fractions (fm) of CYP3A and FMO3 (fmCYP3A:fmFMO3 = 10%:90%, 50%:50%, 90%:10%). RESULTS: All six models consistently predicted higher FMO3 expression/activity in children, reaching a maximum at the age of 2 years with an approximately threefold difference compared with adults. Different trajectories of FMO3 ontogeny in infants < 4 months of age were predicted by the six models, likely due to limited observations for this age range. Use of this  in vivo FMO3 ontogeny function improved prediction of risdiplam PK in children compared to in vitro FMO3 ontogeny functions. The simulations of theoretical dual CYP3A-FMO3 substrates predicted comparable or decreased CYP3A-victim DDI propensity in children compared to adults across the range of fm values. Refinement of FMO3 ontogeny in the risdiplam model had no impact on the previously predicted low CYP3A-victim or -perpetrator DDI risk of risdiplam in children. CONCLUSION: Mech-PPK modelling successfully estimated in vivo FMO3 ontogeny from risdiplam data collected from 525 subjects aged 2 months-61 years. To our knowledge, this is the first investigation of in vivo FMO3 ontogeny by population approach using comprehensive data covering a wide age range. Derivation of a robust in vivo FMO3 ontogeny function has significant implications on the prospective prediction of PK and DDI in children for other FMO3 substrates in the future, as illustrated in the current study for FMO3 and/or dual CYP3A-FMO3 substrates. CLINICAL TRIAL REGISTRY NUMBERS: NCT02633709, NCT03032172, NCT02908685, NCT02913482, NCT03988907.

Model-Based Drug-Drug Interaction Extrapolation Strategy From Adults to Children: Risdiplam in Pediatric Patients With Spinal Muscular Atrophy.

Risdiplam (Evrysdi) improves motor neuron function in patients with spinal muscular atrophy (SMA) and has been approved for the treatment of patients ≥2 months old. Risdiplam exhibits time-dependent inhibition of cytochrome P450 (CYP) 3A in vitro. While many pediatric patients receive risdiplam, a drug-drug interaction (DDI) study in pediatric patients with SMA was not feasible. Therefore, a novel physiologically-based pharmacokinetic (PBPK) model-based strategy was proposed to extrapolate DDI risk from healthy adults to children with SMA in an iterative manner. A clinical DDI study was performed in healthy adults at relevant risdiplam exposures observed in children. Risdiplam caused an 1.11-fold increase in the ratio of midazolam area under the curve with and without risdiplam (AUCR)), suggesting an 18-fold lower in vivo CYP3A inactivation constant compared with the in vitro value. A pediatric PBPK model for risdiplam was validated with independent data and combined with a validated midazolam pediatric PBPK model to extrapolate DDI from adults to pediatric patients with SMA. The impact of selected intestinal and hepatic CYP3A ontogenies on the DDI susceptibility in children relative to adults was investigated. The PBPK analysis suggests that primary CYP3A inhibition by risdiplam occurs in the intestine rather than the liver. The PBPK-predicted risdiplam CYP3A inhibition risk in pediatric patients with SMA aged 2 months-18 years was negligible (midazolam AUCR of 1.09-1.18) and included in the US prescribing information of risdiplam. Comprehensive evaluation of the sensitivity of predicted CYP3A DDI on selected intestinal and hepatic CYP3A ontogeny functions, together with PBPK model-based strategy proposed here, aim to guide and facilitate DDI extrapolations in pediatric populations.

Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making.

BACKGROUND AND OBJECTIVE: Entrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers. METHODS: A PBPK model was established in Simcyp® Simulator. The initial model based on in vitro-in vivo extrapolation was refined using sensitivity analysis and non-linear mixed effects modeling to optimize parameter estimates and to improve model fit to data from a clinical drug-drug interaction study with the strong CYP3A4 inhibitor, itraconazole. The model was subsequently qualified against clinical data, and the final qualified model used to simulate the effects of moderate to strong CYP3A4 inhibitors and inducers on entrectinib and M5 pharmacokinetics. RESULTS: The final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%. CONCLUSIONS: The model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making.

Model-Based Assessments of CYP-Mediated Drug-Drug Interaction Risk of Alectinib: Physiologically Based Pharmacokinetic Modeling Supported Clinical Development.

Alectinib is a selective anaplastic lymphoma kinase (ALK) inhibitor approved for the treatment of ALK-positive non-small cell lung cancer. Alectinib and its major active metabolite M4 exhibited drug-drug interaction (DDI) potential through cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C8 in vitro. Clinical relevance of the DDI risk was investigated as part of a rapid development program to fulfill the breakthrough therapy designation. Therefore, a strategy with a combination of physiologically based pharmacokinetic (PBPK) modeling and limited clinical trials focused on generating informative data for modeling was made to ensure extrapolation ability of DDI risk. The PBPK modeling has provided mechanistic insight into the low victim DDI risk of alectinib through CYP3A4 by a novel two-dimensional analysis for fmCYP3A4 and FG , and demonstrated negligible CYPs 2C8 and 3A4 enzyme-modulating effects at clinically relevant exposure. This work supports that alectinib can be prescribed without dose adjustment for CYP-mediated DDI liabilities.

Effect of Hepatic Impairment on the Pharmacokinetics of Alectinib.

Alectinib is approved and recommended as the preferred first-line treatment for patients with anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer. The effect of hepatic impairment on the pharmacokinetics (PK) of alectinib was assessed with physiologically based PK modeling prospectively and in a clinical study. An open-label study (NCT02621047) investigated a single 300-mg dose of alectinib in moderate (n = 8) and severe (n = 8) hepatic impairment (Child-Pugh B/C), and healthy subjects (n = 12) matched for age, sex, and body weight. Physiologically based PK modeling was conducted prospectively to inform the clinical study design and support the use of a lower dose and extended PK sampling in the study. PK parameters were calculated for alectinib, its major similarly active metabolite, M4, and the combined exposure of alectinib and M4. Unbound concentrations were assessed at 6 and 12 hours postdose. Administration of alectinib to subjects with hepatic impairment increased the area under the plasma concentration-time curve from time 0 to infinity of the combined exposure of alectinib and M4 to 136% (90% confidence interval [CI], 94.7-196) and 176% (90%CI 98.4-315), for moderate and severe hepatic impairment, respectively, relative to matched healthy subjects. Unbound concentrations for alectinib and M4 did not appear substantially different between hepatic-impaired and healthy subjects. Moderate hepatic impairment had only a modest, not clinically significant effect on alectinib exposure, while the higher exposure observed in severe hepatic impairment supports a dose adjustment in this population.

Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective.

This work provides a perspective on the qualification and verification of physiologically based pharmacokinetic (PBPK) platforms/models intended for regulatory submission based on the collective experience of the Simcyp Consortium members. Examples of regulatory submission of PBPK analyses across various intended applications are presented and discussed. European Medicines Agency (EMA) and US Food and Drug Administration (FDA) recent draft guidelines regarding PBPK analyses and reporting are encouraging, and to advance the use and acceptability of PBPK analyses, more clarity and flexibility are warranted.

Progress in Prediction and Interpretation of Clinically Relevant Metabolic Drug-Drug Interactions: a Minireview Illustrating Recent Developments and Current Opportunities.

PURPOSE OF REVIEW: This review gives a perspective on the current "state of the art" in metabolic drug-drug interaction (DDI) prediction. We highlight areas of successful prediction and illustrate progress in areas where limits in scientific knowledge or technologies prevent us from having full confidence. RECENT FINDINGS: Several examples of success are highlighted. Work done for bitopertin shows how in vitro and clinical data can be integrated to give a model-based understanding of pharmacokinetics and drug interactions. The use of interpolative predictions to derive explicit dosage recommendations for untested DDIs is discussed using the example of ibrutinib, and the use of DDI predictions in lieu of clinical studies in new drug application packages is exemplified with eliglustat and alectinib. Alectinib is also an interesting case where dose adjustment is unnecessary as the activity of a major metabolite compensates sufficiently for changes in parent drug exposure. Examples where "unusual" cytochrome P450 (CYP) and non-CYP enzymes are responsible for metabolic clearance have shown the importance of continuing to develop our repertoire of in vitro regents and techniques. The time-dependent inhibition assay using human hepatocytes suspended in full plasma allowed improved DDI predictions, illustrating the importance of continued in vitro assay development and refinement. SUMMARY: During the past 10 years, a highly mechanistic understanding has been developed in the area of CYP-mediated metabolic DDIs enabling the prediction of clinical outcome based on preclinical studies. The combination of good quality in vitro data and physiologically based pharmacokinetic modeling may now be used to evaluate DDI risk prospectively and are increasingly accepted in lieu of dedicated clinical studies.

Clinical Drug-Drug Interactions Through Cytochrome P450 3A (CYP3A) for the Selective ALK Inhibitor Alectinib.

The efficacy and safety of alectinib, a central nervous system-active and selective anaplastic lymphoma kinase (ALK) inhibitor, has been demonstrated in patients with ALK-positive (ALK+) non-small cell lung cancer (NSCLC) progressing on crizotinib. Alectinib is mainly metabolized by cytochrome P450 3A (CYP3A) to a major similarly active metabolite, M4. Alectinib and M4 show evidence of weak time-dependent inhibition and small induction of CYP3A in vitro. We present results from 3 fixed-sequence studies evaluating drug-drug interactions for alectinib through CYP3A. Studies NP28990 and NP29042 enrolled 17 and 24 healthy subjects, respectively, and investigated potent CYP3A inhibition with posaconazole and potent CYP3A induction through rifampin, respectively, on the single oral dose pharmacokinetics (PK) of alectinib. A substudy of the global phase 2 NP28673 study enrolled 15 patients with ALK+ NSCLC to determine the effect of multiple doses of alectinib on the single oral dose PK of midazolam, a sensitive substrate of CYP3A. Potent CYP3A inhibition or induction resulted in only minor effects on the combined exposure of alectinib and M4. Multiple doses of alectinib did not influence midazolam exposure. These results suggest that dose adjustments may not be needed when alectinib is coadministered with CYP3A inhibitors or inducers or for coadministered CYP3A substrates.