Acute coronary syndromes (ACS) remain life-threatening disorders that are associated with high morbidity and mortality. Dual-antiplatelet therapy with aspirin and clopidogrel has shown to reduce cardiovascular events in patients with ACS. However, there is substantial inter-individual variability in response to clopidogrel treatment in addition to prolonged recovery of platelet reactivity as a result of irreversible binding to P2Y12 receptors. This high inter-individual variability in treatment response has primarily been associated with genetic polymorphisms in the genes encoding for cytochrome (CYP) 2C19 that affect clopidogrel’s pharmacokinetics. While FDA has issued a boxed warning for CYP2C19 poor metabolizers due to a potentially reduced efficacy in these patients, results from multivariate analyses suggest that additional factors, including age, sex, obesity, concurrent diseases and drug-drug interactions, may all contribute to the overall between-subject variability in treatment response. However, the extent to which each of these factors contributes to the overall variability and how they are interrelated is currently unclear. The objective of this review article is to provide a comprehensive update on the different factors that influence clopidogrel’s pharmacokinetics and pharmacodynamics and how they mechanistically contribute to inter-individual differences in response to clopidogrel treatment.

On May 29, 2020, the FDA approved atezolizumab for use in combination with bevacizumab, for the treatment of adult patients with unresectable locally advanced or metastatic hepatocellular carcinoma (HCC) with no prior systemic treatment. The approval was based on data from Study IMbrave150, which randomly allocated (2:1) patients to receive either atezolizumab plus bevacizumab (atezolizumab-bevacizumab) or sorafenib. Overall survival (OS) and independently assessed progression-free survival (PFS) in the intent-to-treat population were the primary endpoints. At the time of the primary analysis, the estimated median OS could not be estimated in the atezolizumab-bevacizumab arm and was 13.2 months in the sorafenib arm [HR, 0.58; 95% confidence interval (CI), 0.42–0.79]. The estimated median PFS was 6.8 months (95% CI, 5.8–8.3) and 4.3 months (95% CI, 4.0–5.6) in the atezolizumab-bevacizumab and sorafenib arms, respectively. Adverse reactions occurring in >20% of patients receiving atezolizumab-bevacizumab were hypertension, fatigue/asthenia, and proteinuria. Adverse reactions occurring in >20% of patients receiving sorafenib were palmar-plantar erythrodysesthesia, diarrhea, hypertension, and decreased appetite. Hemorrhage was reported more frequently in patients receiving atezolizumab-bevacizumab (25%) than in patients receiving sorafenib (17%). An evaluation for the presence of varices is recommended within 6 months of initiation of atezolizumab-bevacizumab in patients with HCC. Approval of atezolizumab-bevacizumab is likely to change the treatment paradigm for HCC, given that treatment with atezolizumab-bevacizumab resulted in improved OS and PFS compared with sorafenib, an accepted standard of care for first-line treatment of patients with unresectable HCC. See related commentary by Castet et al., p. 1827

On May 24, 2019, the FDA granted regular approval to alpelisib in combination with fulvestrant for postmenopausal women, and men, with hormone receptor (HR)-positive, HER2-negative, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA)-mutated, advanced or metastatic breast cancer as detected by an FDA-approved test following progression on or after an endocrine-based regimen. Approval was based on the SOLAR-1 study, a randomized, double-blind, placebo-controlled trial of alpelisib plus fulvestrant versus placebo plus fulvestrant. The primary endpoint was investigator-assessed progression-free survival (PFS) per RECIST v1.1 in the cohort of trial participants whose tumors had a PIK3CA mutation. The estimated median PFS by investigator assessment in the alpelisib plus fulvestrant arm was 11 months [95% confidence interval (CI), 7.5–14.5] compared with 5.7 months (95% CI, 3.7–7.4) in the placebo plus fulvestrant arm (HR, 0.65; 95% CI, 0.50–0.85; two-sided P = 0.001). The median overall survival was not yet reached for the alpelisib plus fulvestrant arm (95% CI, 28.1–NE) and was 26.9 months (95% CI, 21.9–NE) for the fulvestrant control arm. No PFS benefit was observed in trial participants whose tumors did not have a PIK3CA mutation (HR, 0.85; 95% CI, 0.58–1.25). The most common adverse reactions, including laboratory abnormalities, on the alpelisib plus fulvestrant arm were increased glucose, increased creatinine, diarrhea, rash, decreased lymphocyte count, increased gamma glutamyl transferase, nausea, increased alanine aminotransferase, fatigue, decreased hemoglobin, increased lipase, decreased appetite, stomatitis, vomiting, decreased weight, decreased calcium, decreased glucose, prolonged activated partial thromboplastin time, and alopecia.

Abstract. Disease-mediated therapeutic protein-drug interactions have recently gained attention from regulatory agencies and pharmaceutical industries in the development of new biological products. In this study, we developed a physiologically based pharmacokinetic (PBPK) model using SimCYP to predict the impact of elevated interleukin-6 (IL-6) levels on cytochrome P450 (CYP) enzymes and the treatment effect of an anti-IL-6 monoclonal antibody, sirukumab, in patients with rheumatoid arthritis (RA). A virtual RA patient population was first constructed by incorporating the impact of systemic IL-6 level on hepatic and intestinal expression of multiple CYP enzymes with information from in vitro studies. Then, a PBPK model for CYP enzyme substrates was developed for healthy adult subjects. After incorporating the virtual RA patient population, the PBPK model was applied to quantitatively predict pharmacokinetics of multiple CYP substrates in RA patients before and after sirukumab treatment from a clinical cocktail drug interaction study. The results suggested that, compared with observed clinical data, changes in systemic exposure to multiple CYP substrates by anti-IL-6 treatment in virtual RA patients have been reasonably captured by the PBPK model, as manifested by modulations in area under plasma concentration versus time curves for midazolam, omeprazole, S-warfarin, and caffeine. This PBPK model reasonably captured the modulation effect of IL-6 and sirukumab on activity of CYP3A, CYP2C9, CYP2C19, and CYP1A2 and holds the potential to be utilized to assess the modulation effect of sirukumab on the metabolism and pharmacokinetics of concomitant small-molecule drugs in RA patients.

T-cell redirecting bispecific antibodies (bsAbs) or antibody-derived agents that combine tumor antigen recognition with CD3-mediated T cell recruitment are highly potent tumor-killing molecules. Despite the tremendous progress achieved in the last decade, development of such bsAbs still faces many challenges. This work aimed to develop a mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) modeling framework that can be used to assist the development of T-cell redirecting bsAbs. A Target cell-Biologics-Effector cell (TBE) complex-based cell killing model was developed using in vitro and in vivo data, which incorporates information on binding affinities of bsAbs to CD3 and target receptors, expression levels of CD3 and target receptors, concentrations of effector and target cells, as well as respective physiological parameters. This TBE model can simultaneously evaluate the effect of multiple system-specific and drug-specific factors on the T-cell redirecting bsAb exposure–response relationship on a physiological basis; it reasonably captured multiple reported in vitro cytotoxicity data, and successfully predicted the effect of some key factors on in vitro cytotoxicity assays and the efficacious dose of blinatumomab in humans. The mechanistic nature of this model uniquely positions it as a knowledge-based platform that can be readily expanded to guide target selection, drug design, candidate selection and clinical dosing regimen projection, and thus support the overall discovery and development of T-cell redirecting bsAbs.

Clopidogrel (Plavix®), is a widely used antiplatelet agent, which shows high inter-individual variability in treatment response in patients following the standard dosing regimen. In this study, a physiology-directed population pharmacokinetic/pharmacodynamic (PK/PD) model was developed based on clopidogrel and clopidogrel active metabolite (clop-AM) data from the PAPI and the PGXB2B studies using a step-wise approach in NONMEM (version 7.2). The developed model characterized the in vivo disposition of clopidogrel, its bioactivation into clop-AM in the liver and subsequent platelet aggregation inhibition in the systemic circulation reasonably well. It further allowed the identification of covariates that significantly impact clopidogrel’s dose–concentration–response relationship. In particular, CYP2C19 intermediate and poor metabolizers converted 26.2% and 39.5% less clopidogrel to clop-AM, respectively, compared to extensive metabolizers. In addition, CES1 G143E mutation carriers have a reduced CES1 activity (82.9%) compared to wild-type subjects, which results in a significant increase in clop-AM formation. An increase in BMI was found to significantly decrease clopidogrel’s bioactivation, whereas increased age was associated with increased platelet reactivity. Our PK/PD model analysis suggests that, in order to optimize clopidogrel dosing on a patient-by-patient basis, all of these factors have to be considered simultaneously, e.g. by using quantitative clinical pharmacology tools.

Therapeutic monoclonal antibodies (mAb) targeting soluble inflammatory cytokines exert their pharmacological effects in rheumatoid arthritis through binding and neutralizing free cytokines in target tissue sites. Therefore suppression of free cytokines in such sites directly relates to the magnitude of therapeutic response. Although the interrelationships between mAb and cytokines have been examined in the systemic circulation, less is known about the interaction of mAb and cytokines in inflamed joints. In the present study, the interplay between the mAb, CNTO 345, and its target IL-6 in serum as well as ankle joint synovial fluid were characterized in collagen-induced arthritic mice. A minimal physiologically-based pharmacokinetic model with target-mediated drug disposition (TMDD) features in serum and ankle joint synovial fluid was developed for the assessment of the TMDD dynamics of CNTO 345 and IL-6. Our model indicates that TMDD kinetics in ankle joints differ greatly from that in serum. The differences can be attributed to the limited tissue distribution of CNTO 345 in ankle joint synovial fluid, the significant rise of the IL-6 baseline in ankle joint synovial fluid in comparison with serum, and the relative time-scales of elimination rates between CNTO 345, free IL-6 and CNTO 345-IL-6 complex in serum and ankle joint synovial fluid.

The interleukin (IL)-23/T17/IL-17 immune pathway has been identified to play an important role in the pathogenesis of psoriasis. Many therapeutic proteins targeting IL-23 or IL-17 are currently under development for the treatment of psoriasis. In the present study, a mechanistic pharmacokinetics (PK)/pharmacodynamics (PD) study was conducted to assess the target-binding and disposition kinetics of a monoclonal antibody (mAb), CNTO 3723, and its soluble target, mouse IL-23, in an IL-23-induced psoriasis-like mouse model. A minimal physiologically based pharmacokinetic model with target-mediated drug disposition features was developed to quantitatively assess the kinetics and interrelationship between CNTO 3723 and exogenously administered, recombinant mouse IL-23 in both serum and lesional skin site. Furthermore, translational applications of the developed model were evaluated with incorporation of human PK for ustekinumab, an anti-human IL-23/IL-12 mAb developed for treatment of psoriasis, and human disease pathophysiology information in psoriatic patients. The results agreed well with the observed clinical data for ustekinumab. Our work provides an example on how mechanism-based PK/PD modeling can be applied during early drug discovery and how preclinical data can be used for human efficacious dose projection and guide decision making during early clinical development of therapeutic proteins.