The low productivity and escalating costs of drug development have been well documented over the past several years. Less than 10% of new compounds that enter clinical trials ultimately make it to the market, and many more fail in the preclinical stages of development. These challenges in the "critical path" of drug development are discussed in a 2004 publication by the US Food and Drug Administration. The document emphasizes new tools and various opportunities to improve drug development. One of the opportunities recommended is the application of "model-based drug development (MBDD)." This paper discusses what constitutes the key elements of MBDD and how these elements should fit together to inform drug development strategy and decision-making.

Covariate selection is an activity routinely performed during pharmacometric analysis. Many are familiar with the stepwise procedures, but perhaps not as many are familiar with some of the issues associated with such methods. Recently, attention has focused on selection procedures that do not suffer from these issues and maintain good predictive properties. In this review, we endeavour to put the main variable selection procedures into a framework that facilitates comparison. We highlight some issues that are unique to pharmacometric analyses and provide some thoughts and strategies for pharmacometricians to consider when planning future analyses.

Our findings suggest a relationship between pruritus severity and anger in CIU. Furthermore, our results indicate a relationship between pruritus severity and depression in psoriasis.

An exposure-response (E-R) analysis using linear mixed effects modeling was conducted on data from a thorough QTc trial for asenapine in 148 patients with schizophrenia. In a parallel design, patients received asenapine 5 mg twice daily (BID) for 10 days (10d) followed by 10 mg BID (6d), asenapine 15 mg BID (10d) followed by 20 mg BID (6d), quetiapine 375 mg BID (for assay sensitivity; 16d) or placebo (16d). Triplicate 12-lead electrocardiograms and concentration measurements were obtained on day -1 (baseline), 1, 10, and 16 at 8 scheduled times on each day. At mean C(max) for all asenapine doses, the E-R model predicted that the mean QTcF increase was less than 5 milliseconds, the International Conference on Harmonisation-established threshold for clinical concern. The model predicted a mean increase of 7 to 8 milliseconds for quetiapine. The corresponding upper bounds of the 95% confidence intervals were 7.5 milliseconds and 11.2 milliseconds for asenapine and quetiapine, respectively.

BackgroundIn the phase III METEOR trial, tyrosine kinase inhibitor cabozantinib significantly improved progression-free survival (PFS), objective response rate (ORR), and overall survival compared to everolimus in patients with advanced renal cell carcinoma (RCC) who had received prior VEGFR inhibitor therapy. In METEOR, RCC patients started at a daily 60-mg cabozantinib tablet (Cabometyx™) dose but could reduce to 40- or 20-mg to achieve a tolerated exposure.Objectives and methodsExposure–response (ER) models were developed to characterize the relationship between cabozantinib at clinically relevant exposures in RCC patients enrolled in METEOR and efficacy (PFS and tumor response) and safety endpoints.ResultsCompared to the average steady-state cabozantinib concentration for a 60-mg dose, exposures at simulated 40- and 20-mg starting doses were predicted to result in higher risk of disease progression or death [hazard ratios (HRs) of 1.10 and 1.39, respectively], lower maximal median reduction in tumor size (− 11.9 vs − 9.1 and − 4.5%, respectively), and lower ORR (19.1 vs 15.6 and 8.7%, respectively). The 60-mg exposure was also associated with higher risk for selected adverse events (AEs) palmar-plantar erythrodysesthesia syndrome (grade ≥ 1), fatigue/asthenia (grade ≥ 3), diarrhea (grade ≥ 3), and hypertension (predicted HRs of 2.21, 2.01, 1.78, and 1.85, respectively) relative to the predicted average steady-state cabozantinib concentration for a 20-mg starting dose.ConclusionER modeling predicted that cabozantinib exposures in RCC patients at the 60-mg starting dose would provide greater anti-tumor activity relative to exposures at simulated 40- and 20-mg starting doses that were associated with decreased rates of clinically relevant AEs.Electronic supplementary materialThe online version of this article (10.1007/s00280-018-3579-7) contains supplementary material, which is available to authorized users.

To describe the pregabalin exposure-adverse event (AE) (dizziness) relationship in patients with generalized anxiety disorder, separate models were developed for the incidence of AE and for the conditional severity of AE, given that an AE has occurred using patient data from six clinical studies. The incidence component was modeled using a nonlinear logistic regression model. The conditional severity component was modeled as an ordered categorical variable with a proportional odds model to capture the severity on any given day. A Markov element was introduced to account for the correlation between neighboring observations. The proportional odds model including a time course of appearance and disappearance of AE could adequately describe the time course of probability of dizziness. Incorporating a transition model including Markov elements improved the model fit and greatly improved the predictability of the time course of probability of dizziness.

Extended‐release (XR) formulations enable less frequent dosing vs. conventional (e.g., immediate release (IR)) formulations. Regulatory registration of such formulations typically requires pharmacokinetic (PK) and clinical efficacy data. Here we illustrate a model‐informed, exposure–response (E‐R) approach to translate controlled trial data from one formulation to another without a phase III trial, using a tofacitinib case study. Tofacitinib is an oral Janus kinase (JAK) inhibitor for the treatment of rheumatoid arthritis (RA). E‐R analyses were conducted using validated clinical endpoints from phase II dose–response and nonclinical dose fractionation studies of the IR formulation. Consistent with the delay in clinical response dynamics relative to PK, average concentration was established as the relevant PK parameter for tofacitinib efficacy and supported pharmacodynamic similarity. These evaluations, alongside demonstrated equivalence in total systemic exposure between IR and XR formulations, provided the basis for the regulatory approval of tofacitinib XR once daily by the US Food and Drug Administration.

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