Simvastatin is a commonly prescribed medication and a sensitive CYP3A4 substrate requiring dosage modification with CYP3A4 precipitants. Unlike other CYP3A4 substrates, grapefruit juice (GFJ) causes the largest increase in simvastatin exposure of any CYP3A4 inhibitor, leading to misunderstanding of simvastatin fraction escaping CYP3A4 metabolism in the gut (Fg, CYP3A4) and fraction metabolized by CYP3A4 in the liver (fm,CYP3A4). Simvastatin is a prodrug that is converted to the active simvastatin acid, though the mechanisms responsible for in vivo simvastatin acid formation are not well-understood. GFJ also decreases the simvastatin acid:simvastatin exposure ratio, suggesting inhibition of simvastatin acid formation. In the current work, we used a static approach to define simvastatin CYP3A4 parameters, using clinical data with index substrate midazolam; estimated simvastatin Fg,CYP3A4 and fm,CYP3A4 were 0.4 and 0.9, respectively. In vitro data assessing the stability of simvastatin and simvastatin acid demonstrated rapid conversion in gastric fluid that was highly pH-dependent. A simvastatin PBPK model was constructed incorporating these CYP3A4 parameters and simvastatin acid formation in stomach, intestine and plasma. The model reproduced the nonlinear pharmacokinetics of simvastatin and CYP3A4 precipitant effects, thus qualifying the model for prediction of CYP3A4-mediated interactions on both simvastatin and simvastatin acid. Simvastatin overall Fg was estimated as 0.2, lower than the Fg,CYP3A4 due to additional intestinal esterase-mediated formation of simvastatin acid. The simvastatin-GFJ effect was explained by inhibition of this intestinal simvastatin acid formation, along with CYP3A4 inhibition. The unique effect of food on the simvastatin acid:simvastatin exposure ratio could also be replicated using this PBPK model.

Dulaglutide, a long-acting glucagon-like peptide-1 (GLP-1) receptor agonist, is approved for improving glycemic control and reducing cardiovascular risks in patients with type 2 diabetes mellitus (T2DM). This research investigates the effect of dulaglutide on gastric emptying and its impact on the pharmacokinetics (PK) of orally administered molecules utilizing a combination of population pharmacokinetic (PopPK) and physiologically based pharmacokinetic (PBPK) modeling approaches. In clinical studies, the gastric emptying delay (GED) was evaluated in healthy participants and patients with T2DM at various dose levels of dulaglutide. A PopPK model estimated the exposure-dependent delay in gastric emptying, which was then input into the orally administered small molecule PBPK models. These PBPK models, informed by internal clinical studies and publicly available data, quantified the effect of dulaglutide-induced GED on the area under the curve (AUC), maximum concentration (Cmax), and time to maximum concentration (tmax) of the co-administered drugs. The modeling approach was verified for reproducing observed GED-mediated drug-drug interactions (DDIs) at low doses of dulaglutide and to predict DDIs at a 4.5 mg dulaglutide dose. The clinical studies demonstrated that the 1.5 mg dulaglutide dose has no clinically relevant effect on the pharmacokinetics of small molecules, and the modeling led to a similar conclusion at 4.5 mg dulaglutide. This work demonstrates that modeling approaches can be used to predict potential GLP-1-mediated DDIs related to gastric emptying delay, increasing the efficiency of the clinical pharmacology programs.

Tadalafil, a phosphodiesterase 5 inhibitor, is being investigated as a treatment for pulmonary arterial hypertension (PAH) in children aged 6 months to less than 18 years. Tadalafil pharmacokinetic (PK) data in children less than 2 years old are unavailable, therefore a physiologically based pharmacokinetic (PBPK) model was developed to enable estimation of tadalafil doses in children less than 2 years old. The model was verified in adults and extended for use in children by modifying CYP3A-mediated intrinsic clearance to include CYP3A7. To account for co-dosing of the commonly prescribed moderate CYP3A4 inducer bosentan, predicted exposures were increased by a factor of 1.54 based on changes in exposure in adults with PAH. This factor was predictable using a bosentan PBPK model. The tadalafil model was verified in children aged greater than or equal to 2 years by comparing predicted and observed exposures. Tadalafil doses for children less than 2 years old were calculated as target area under the concentration curve from zero to 24 h (AUC(0-24))/predicted AUC(0-24), with target AUC(0-24) of 10,000 ng*h/ml based on adult 40 mg single dose exposures determined in patients without bosentan background treatment. These doses were 2 mg, 3 mg, 4 mg, and 6 mg, respectively, for children aged birth to less than 1 month, 1 month to less than 6 months, 6 months to less than 1 year, and 1 to less than 2 years. Due to uncertainties in CYP maturation, a nonmechanistic steady-state volume scalar, and lack of PK data in children less than 2 years old, accumulation of tadalafil to steady-state in children less than 2 years was not verifiable. Safety of proposed doses is supported by postmarketing research and investigator-led trials.

Abemaciclib, a selective inhibitor of cyclin-dependent kinases 4 and 6, is metabolized mainly by cytochrome P450 (CYP)3A4. Clinical studies were performed to assess the impact of strong inhibitor (clarithromycin) and inducer (rifampin) on the exposure of abemaciclib and active metabolites. A physiologically based pharmacokinetic (PBPK) model incorporating the metabolites was developed to predict the effect of other strong and moderate CYP3A4 inhibitors and inducers. Clarithromycin increased the area under the plasma concentration-time curve (AUC) of abemaciclib and potency-adjusted unbound active species 3.4-fold and 2.5-fold, respectively. Rifampin decreased corresponding exposures 95% and 77%, respectively. These changes influenced the fraction metabolized via CYP3A4 in the model. An absolute bioavailability study informed the hepatic and gastric availability. In vitro data and a human radiolabel study determined the fraction and rate of formation of the active metabolites as well as absorption-related parameters. The predicted AUC ratios of potency-adjusted unbound active species with rifampin and clarithromycin were within 0.7- and 1.25-fold of those observed. The PBPK model predicted 3.78- and 7.15-fold increases in the AUC of the potency-adjusted unbound active species with strong CYP3A4 inhibitors itraconazole and ketoconazole, respectively; and 1.62- and 2.37-fold increases with the concomitant use of moderate CYP3A4 inhibitors verapamil and diltiazem, respectively. The model predicted modafinil, bosentan, and efavirenz would decrease the AUC of the potency-adjusted unbound active species by 29%, 42%, and 52%, respectively. The current PBPK model, which considers changes in unbound potency-adjusted active species, can be used to inform dosing recommendations when abemaciclib is coadministered with CYP3A4 perpetrators.

Immunogenicity is a major challenge in drug development and patient care. Currently, most efforts are dedicated to the elimination of the unwanted immune responses through T-cell epitope prediction and protein engineering. However, because it is unlikely that this approach will lead to complete eradication of immunogenicity, we propose that quantitative systems pharmacology models should be developed to predict and manage immunogenicity. The potential impact of such a mechanistic model-based approach is precedented by applications of physiologically-based pharmacokinetics.

We verified a physiologically‐based pharmacokinetic (PBPK) model to predict cytochrome P450 3A4/5‐mediated drug‐drug interactions (DDIs). A midazolam (MDZ)–ketoconazole (KTZ) interaction study in 24 subjects selected by CYP3A5 genotype, and liquid chromatography and mass spectroscopy quantification of CYP3A4/5 abundance from independently acquired and genotyped human liver (n = 136) and small intestinal (N = 12) samples, were conducted. The observed CYP3A5 genetic effect on MDZ systemic and oral clearance was successfully replicated by a mechanistic framework incorporating the proteomics‐informed CYP3A abundance and optimized small intestinal CYP3A4 abundance based on MDZ intestinal availability (FG) of 0.44. Furthermore, combined with a modified KTZ PBPK model, this framework recapitulated the observed geometric mean ratio of MDZ area under the curve (AUCR) following 200 or 400 mg KTZ, which was, respectively, 2.7–3.4 and 3.9–4.7‐fold in intravenous administration and 11.4–13.4 and 17.0–19.7‐fold in oral administration, with AUCR numerically lower (P > 0.05) in CYP3A5 expressers than nonexpressers. In conclusion, the developed mechanistic framework supports dynamic prediction of CYP3A‐mediated DDIs in study planning by bridging DDIs between CYP3A5 expressers and nonexpressers.

The drug–drug interaction profile of atorvastatin confirms that disposition is determined by cytochrome P450 (CYP) 3A4 and organic anion transporting polypeptides (OATPs). Drugs that affect gastric emptying, including dulaglutide, also affect atorvastatin pharmacokinetics (PK). Atorvastatin is a carboxylic acid that exists in equilibrium with a lactone form in vivo. The purpose of this work was to assess gastric acid–mediated lactone equilibration of atorvastatin and incorporate this into a physiologically‐based PK (PBPK) model to describe atorvastatin acid, lactone, and their major metabolites. In vitro acid‐to‐lactone conversion was assessed in simulated gastric fluid and included in the model. The PBPK model was verified with in vivo data including CYP3A4 and OATP inhibition studies. Altering the gastric acid–lactone equilibrium reproduced the change in atorvastatin PK observed with dulaglutide. The model emphasizes the need to include gastric acid–lactone conversion and all major atorvastatin‐related species for the prediction of atorvastatin PK.

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.

Aims: Drug–drug interaction studies were used to estimate CYP3A4-dependent clearance of LY2623091. Methods: in a cross-over design, healthy adults received a single 6-mg dose of LY2623091 at baseline. Itraconazole (200 mg twice on day 1 then daily × 19 days; n = 16) and diltiazem (240 mg Extended Release daily × 13 days; n = 16) were given. On days 6 and 4, respectively, LY2623091 was dosed 1 h after itraconazole/diltiazem. Pharmacokinetic samples were obtained and static and dynamic models were used to assess interaction. Results: Area under the concentration–time curve for LY2623091 increased 2.2-fold with itraconazole and 1.4-fold with diltiazem. Maximum plasma concentration did not change. The physiologically based pharmacokinetic model overpredicted itraconazole and hydroxy–itraconazole concentrations. Extraction by CYP3A4 was ∼0.5; gut wall extraction was negligible. Conclusion: Interaction risk requires early clinical assessment to quantify the candidate drug. (Clinical trial registration number: NCT02300259). Data deposition: deposition pending.

LY2623091 is a selective, orally active, nonsteroidal, competitive mineralocorticoid receptor antagonist that blocks the actions of aldosterone and other mineralocorticoid receptor ligands at the receptor level. The aim of this work was to explore and establish a population pharmacokinetic model, quantify the degree of interindividual variability, and identify significant disease-, patient-, and study-specific covariates that alter the disposition of LY2623091. The data included concentrations from 294 healthy subjects and patients with hypertension and/or chronic kidney disease (CKD), sampled in 5 phase 1 and 2 studies. The pharmacokinetics of LY2623091 was well described by a 2-compartment model with first-order absorption and elimination. Formulation (on oral bioavailability) as well as weight and age (both on apparent central volume of distribution) were found to be significant covariates. The relative bioavailability of the capsule formulation was 68.4% compared to that of the solution. Hypertension and CKD status were not significant covariates. The pharmacokinetic model suggests that given the same dose, patients with hypertension and/or CKD would receive a similar exposure compared to subjects without these disease conditions.

Using physiologically based pharmacokinetic (PBPK) models to quantitatively predict drug‐drug interaction (DDI) is becoming common practice in drug development. To accurately assess DDI risk, it is important to verify the existing PBPK models of known substrates and inhibitors before applying the models for DDI prediction. Cytochrome P450 (CYP) 2D6 is a major drug metabolizing enzyme responsible for eliminating ~25% of clinically used drugs. Paroxetine is a strong mechanism‐based inhibitor of CYP2D6 and desipramine is a sensitive substrate of the enzyme. Here we verified and improved the Simcyp® models of paroxetine and desipramine for their application in CYP2D6‐mediated DDI prediction. We first examined the performance of existing Simcyp® models in describing drug exposure of paroxetine and desipramine alone. The Simcyp® paroxetine model predicted paroxetine drug exposure within 2 fold difference comparing with clinical data. However, when daily dose was 20 mg or lower, the model under‐predicted paroxetine drug accumulation at steady state, with observed/predicted Cmax and AUC ratio over 1.5 fold. Related parameters, KI and kinact for CYP2D6 mechanism‐based inhibition, were changed from 0.315 μM and 10.2 1/h to 0.067 μM and 11.55 1/h respectively, based on recently published in vitro data1. The new model showed improved prediction of paroxetine exposure at steady state under lower doses. On the other hand, the Simcyp® desipramine model under‐predicted drug clearance in CYP2D6 poor metabolizers (PMs), where renal clearance was the only clearance pathway. Additional systematic clearance of 13.5 L/h was added to the model based on observed clearance in PM subjects. The improved desipramine PBPK model was able to predict desipramine PK in both CYP2D6 extensive metabolizers and PMs. To evaluate the performance of the improved PBPK models of paroxetine and desipramine in predicting CYP2D6‐mediated DDI, we simulated paroxetine‐desipramine interaction in different scenarios and compared the results with observed data. For all simulations, the predicted AUC ratio of desipramine with or without interaction was within 1.25 fold difference with clinical observations. In summary, the improved PBPK models of paroxetine and desipramine can predict drug exposure of the drugs and DDI between paroxetine and desipramine when combined together. This increases our confidence in using the two models to predict CYP2D6‐mediated DDI in other circumstances.Support or Funding InformationThis work is part of a project funded by Eli Lilly & Company.

The k-opioid receptor (KOR) is thought to play an important therapeutic role in a wide range of neuropsychiatric and substance abuse disorders, including alcohol dependence. LY2456302 is a recently developed KOR antagonist with high affinity and selectivity and showed efficacy in the suppression of ethanol consumption in rats. This study investigated brain penetration and KOR target engagement after single oral doses (0.5–25 mg) of LY2456302 in 13 healthy human subjects. Three positron emission tomography scans with the KOR antagonist radiotracer C-LY2795050 were conducted at baseline, 2.5 hours postdose, and 24 hours postdose. LY2456302 was well tolerated in all subjects without serious adverse events. Distribution volume was estimated using the multilinear analysis 1 method for each scan. Receptor occupancy (RO) was derived from a graphical occupancy plot and related to LY2456302 plasma concentration to determine maximum occupancy (rmax) and IC50. LY2456302 dose dependently blocked the binding of C-LY2795050 and nearly saturated the receptors at 10 mg, 2.5 hours postdose. Thus, a dose of 10 mg of LY2456302 appears well suited for further clinical testing. Based on the pharmacokinetic (PK)-RO model, the rmax and IC50 of LY2456302 were estimated as 93%and 0.58 ng/ml to 0.65 ng/ml, respectively. Assuming that rmax is 100%, IC50 was estimated as 0.83 ng/ml.

The k-opioid receptor (KOR) is thought to play an important therapeutic role in a wide range of neuropsychiatric and substance abuse disorders, including alcohol dependence. LY2456302 is a recently developed KOR antagonist with high affinity and selectivity and showed efficacy in the suppression of ethanol consumption in rats. This study investigated brain penetration and KOR target engagement after single oral doses (0.5–25 mg) of LY2456302 in 13 healthy human subjects. Three positron emission tomography scans with the KOR antagonist radiotracer C-LY2795050 were conducted at baseline, 2.5 hours postdose, and 24 hours postdose. LY2456302 was well tolerated in all subjects without serious adverse events. Distribution volume was estimated using the multilinear analysis 1 method for each scan. Receptor occupancy (RO) was derived from a graphical occupancy plot and related to LY2456302 plasma concentration to determine maximum occupancy (rmax) and IC50. LY2456302 dose dependently blocked the binding of C-LY2795050 and nearly saturated the receptors at 10 mg, 2.5 hours postdose. Thus, a dose of 10 mg of LY2456302 appears well suited for further clinical testing. Based on the pharmacokinetic (PK)-RO model, the rmax and IC50 of LY2456302 were estimated as 93%and 0.58 ng/ml to 0.65 ng/ml, respectively. Assuming that rmax is 100%, IC50 was estimated as 0.83 ng/ml.

The κ-opioid receptor (KOR) is thought to play an important therapeutic role in a wide range of neuropsychiatric and substance abuse disorders, including alcohol dependence. LY2456302 is a recently developed KOR antagonist with high affinity and selectivity and showed efficacy in the suppression of ethanol consumption in rats. This study investigated brain penetration and KOR target engagement after single oral doses (0.5–25 mg) of LY2456302 in 13 healthy human subjects. Three positron emission tomography scans with the KOR antagonist radiotracer 11C-LY2795050 were conducted at baseline, 2.5 hours postdose, and 24 hours postdose. LY2456302 was well tolerated in all subjects without serious adverse events. Distribution volume was estimated using the multilinear analysis 1 method for each scan. Receptor occupancy (RO) was derived from a graphical occupancy plot and related to LY2456302 plasma concentration to determine maximum occupancy (rmax) and IC50. LY2456302 dose dependently blocked the binding of 11C-LY2795050 and nearly saturated the receptors at 10 mg, 2.5 hours postdose. Thus, a dose of 10 mg of LY2456302 appears well suited for further clinical testing. Based on the pharmacokinetic (PK)-RO model, the rmax and IC50 of LY2456302 were estimated as 93% and 0.58 ng/ml to 0.65 ng/ml, respectively. Assuming that rmax is 100%, IC50 was estimated as 0.83 ng/ml.

To develop a population physiologically-based pharmacokinetic (PBPK) model for simvastatin (SV) and its active metabolite, simvastatin acid (SVA), that allows extrapolation and prediction of their concentration profiles in liver (efficacy) and muscle (toxicity).

Accumulating evidence indicates that selective antagonism of kappa opioid receptors may provide therapeutic benefit in the treatment of major depressive disorder, anxiety disorders, and substance use disorders. LY2456302 is a high-affinity, selective kappa opioid antagonist that demonstrates >30-fold functional selectivity over mu and delta opioid receptors. The safety, tolerability, and pharmacokinetics (PK) of LY2456302 were investigated following single oral doses (2-60mg), multiple oral doses (2, 10, and 35mg), and when co-administered with ethanol. Plasma concentrations of LY2456302 were measured by liquid chromatography-tandem mass spectrometry method. Safety analyses were conducted on all enrolled subjects. LY2456302 doses were well-tolerated with no clinically significant findings. No safety concerns were seen on co-administration with ethanol. No evidence for an interaction between LY2456302 and ethanol on cognitive-motor performance was detected. LY2456302 displayed rapid oral absorption and a terminal half-life of approximately 30-40hours. Plasma exposure of LY2456302 increased proportionally with increasing doses and reached steady state after 6-8 days of once-daily dosing. Steady-state PK of LY2456302 were not affected by coadministration of a single dose of ethanol. No clinically important changes in maximum concentration (Cmax) or AUC of ethanol (in the presence of LY2456302) were observed.

No consistent method is available for finding stable warfarin maintenance doses and fast stabilization of international normalized ratio (INR) values among healthy subjects in experimental warfarin interaction studies. Using data from an earlier study that targeted a stable INR of 1.5–2.0 to test an interaction, we retrospectively evaluated potential dosing algorithms using all methods available to us to decrease the time needed for INR stabilization, which could be useful for future interaction studies in healthy subjects.