Model-based drug development: strengths, weaknesses, opportunities, and threats for broad application of pharmacometrics in drug development

Clinically practical pharmacometrics computer model to evaluate and personalize pharmacotherapy in pediatric rare diseases: application to Graves' disease

Objectives

Graves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy.

Methods

Retrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis.

Results

Data from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity.

Discussion

We present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

Pharmacometrics: A New Era of Pharmacotherapy and Drug Development in Low- and Middle-Income Countries

Pharmacotherapy, in many cases, is practiced at a suboptimal level of performance in low- and middle-income countries (LMICs) although stupendous amounts of data are available regularly. The process of drug development is time-consuming, costly, and is also associated with loads of hurdles related to the safety concerns of the compounds. This review was conducted with the objective to emphasize the role of pharmacometrics in pharmacotherapy and the drug development process in LMICs for rational drug therapy. Pharmacometrics is widely applied for the rational clinical pharmacokinetic (PK) practice through the population pharmacokinetic (popPK) modeling and physiologically based pharmacokinetic (PBPK) modeling approach. The scope of pharmacometrics practice is getting wider day by day with the untiring efforts of pharmacometricians. The basis for pharmacometrics analysis is the computer-based modeling and simulation of pharmacokinetics/pharmacodynamics (PK/PD) data supplemented by characterization of important aspects of drug safety and efficacy. Pharmacometrics can be considered an invaluable tool not only for new drug development with maximum safety and efficacy but also for dose optimization in clinical settings. Due to the convenience of using sparse and routine patient data, a significant advantage exists in this regard for LMICs which would otherwise lag behind in clinical trials.

Knowledge dissemination and central indexing of resources in pharmacometrics: an ISOP education working group initiative

Pharmacometrics is a constantly evolving field that plays a major role in decision making in drug development and clinical monitoring. Scientists in Pharmacometrics, especially in their early phases of career, are often faced with the challenge of identifying adequate resources for self-training and education. Hence, the ISoP Education Committee through its working group dedicated to Central Indexing and knowledge Dissemination has built a database of worldwide educational programs and most common references in Pharmacometrics.

A tutorial on model informed approaches to cardiovascular safety with focus on cardiac repolarisation

Drugs can affect the cardiovascular (CV) system either as an intended treatment or as an unwanted side effect. In both cases, drug-induced cardiotoxicities such as arrhythmia and unfavourable hemodynamic effects can occur, and be described using mathematical models; such a model informed approach can provide valuable information during drug development and can aid decision-making. However, in order to develop informative models, it is vital to understand CV physiology. The aims of this tutorial are to present (1) key background biological and medical aspects of the CV system, (2) CV electrophysiology, (3) CV safety concepts, (4) practical aspects of development of CV models and (5) regulatory expectations with a focus on using model informed and quantitative approaches to support nonclinical and clinical drug development. In addition, we share several case studies to provide practical information on project strategy (planning, key questions, assumptions setting, and experimental design) and mathematical models development that support decision-making during drug discovery and development.

Exposure-response analysis of rilotumumab in gastric cancer: the role of tumour MET expression

BACKGROUND

Rilotumumab, an investigational, monoclonal antibody, inhibits MET-mediated signalling. In a randomized phase 2 trial of rilotumumab±epirubicin/cisplatin/capecitabine in gastric or oesophagogastric junction cancer, patients receiving rilotumumab showed a trend towards improved survival, especially in MET-positive patients, but no clear dose-response relationship was observed. Exposure-response and biomarker analyses were used for dose selection and to differentiate patient subpopulations that may benefit most from treatment. Here, we analyse rilotumumab exposure-survival and exposure-safety and the impact of MET expression on these relationships.

METHODS

Individual rilotumumab exposure parameters were generated using population pharmacokinetic modelling. Relationships among rilotumumab dose (7.5 and 15 mg kg(-1)), exposure, and clinical outcomes (progression-free survival (PFS) and overall survival (OS)) were evaluated with Cox regression models and Kaplan-Meier plots. MET status and other baseline covariates were evaluated in subgroup and multivariate analyses. Treatment-emergent adverse events were summarised by exposure.

RESULTS

Among MET-positive patients, higher rilotumumab exposure, vs placebo and low exposure, was associated with improved median PFS (80% CI: 7.0 (5.7-9.7) vs 4.4 (2.9-4.9) and 5.5 (4.2-6.8) months) and OS (13.4 (10.6-18.6) vs 5.7 (4.7-10.2) and 8.1 (6.9-11.1) months) without increased toxicity. No rilotumumab benefit was seen among MET-negative patients.

CONCLUSIONS

Rilotumumab had an exposure-dependent treatment effect in patients with MET-positive gastric or oesophagogastric junction cancer.

Dashboard systems: implementing pharmacometrics from bench to bedside

In recent years, there has been increasing interest in the development of medical decision-support tools, including dashboard systems. Dashboard systems are software packages that integrate information and calculations about therapeutics from multiple components into a single interface for use in the clinical environment. Given the high cost of medical care, and the increasing need to demonstrate positive clinical outcomes for reimbursement, dashboard systems may become an important tool for improving patient outcome, improving clinical efficiency and containing healthcare costs. Similarly the costs associated with drug development are also rising. The use of model-based drug development (MBDD) has been proposed as a tool to streamline this process, facilitating the selection of appropriate doses and making informed go/no-go decisions. However, complete implementation of MBDD has not always been successful owing to a variety of factors, including the resources required to provide timely modeling and simulation updates. The application of dashboard systems in drug development reduces the resource requirement and may expedite updating models as new data are collected, allowing modeling results to be available in a timely fashion. In this paper, we present some background information on dashboard systems and propose the use of these systems both in the clinic and during drug development.

Oral biopharmaceutics tools - time for a new initiative - an introduction to the IMI project OrBiTo

OrBiTo is a new European project within the IMI programme in the area of oral biopharmaceutics tools that includes world leading scientists from nine European universities, one regulatory agency, one non-profit research organization, four SMEs together with scientists from twelve pharmaceutical companies. The OrBiTo project will address key gaps in our knowledge of gastrointestinal (GI) drug absorption and deliver a framework for rational application of predictive biopharmaceutics tools for oral drug delivery. This will be achieved through novel prospective investigations to define new methodologies as well as refinement of existing tools. Extensive validation of novel and existing biopharmaceutics tools will be performed using active pharmaceutical ingredient (API), formulations and supporting datasets from industry partners. A combination of high quality in vitro or in silico characterizations of API and formulations will be integrated into physiologically based in silico biopharmaceutics models capturing the full complexity of GI drug absorption. This approach gives an unparalleled opportunity to initiate a transformational change in industrial research and development to achieve model-based pharmaceutical product development in accordance with the Quality by Design concept. Benefits include an accelerated and more efficient drug candidate selection, formulation development process, particularly for challenging projects such as low solubility molecules (BCS II and IV), enhanced and modified-release formulations, as well as allowing optimization of clinical product performance for patient benefit. In addition, the tools emerging from OrBiTo are expected to significantly reduce demand for animal experiments in the future as well as reducing the number of human bioequivalence studies required to bridge formulations after manufacturing or composition changes.

Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity

A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent-based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework—a dynamic knowledge repository—wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline. © 2013 Wiley Periodicals, Inc.

White paper: landscape on technical and conceptual requirements and competence framework in drug/disease modeling and simulation

Pharmaceutical sciences experts and regulators acknowledge that pharmaceutical development as well as drug usage requires more than scientific advancements to cope with current attrition rates/therapeutic failures. Drug disease modeling and simulation (DDM&S) creates a paradigm to enable an integrated and higher-level understanding of drugs, (diseased)systems, and their interactions (systems pharmacology) through mathematical/statistical models (pharmacometrics)¹—hence facilitating decision making during drug development and therapeutic usage of medicines. To identify gaps and challenges in DDM&S, an inventory of skills and competencies currently available in academia, industry, and clinical practice was obtained through survey. The survey outcomes revealed benefits, weaknesses, and hurdles for the implementation of DDM&S. In addition, the survey indicated that no consensus exists about the knowledge, skills, and attributes required to perform DDM&S activities effectively. Hence, a landscape of technical and conceptual requirements for DDM&S was identified and serves as a basis for developing a framework of competencies to guide future education and training in DDM&S.

Mathematical modeling of tumor growth and tumor growth inhibition in oncology drug development

INTRODUCTION

Approaches aiming to model the time course of tumor growth and tumor growth inhibition following a therapeutic intervention have recently been proposed for supporting decision making in oncology drug development. When considered in a comprehensive model-based approach, tumor growth can be included in the cascade of quantitative and causally related markers that lead to the prediction of survival, the final clinical response.

AREAS COVERED

The authors examine articles dealing with the modeling of tumor growth and tumor growth inhibition in both preclinical and clinical settings. In addition, the authors review models describing how pharmacological markers can be used to predict tumor growth and models describing how tumor growth can be linked to survival endpoints.

EXPERT OPINION

Approaches and success stories of application of model-based drug development centered on tumor growth modeling are growing. It is also apparent that these approaches can answer practical questions on drug development more effectively than that in the past. For modeling purposes, some improvements are still needed related to study design and data quality. Further efforts are needed to encourage the mind shift from a simple description of data to the prediction of untested conditions that modeling approaches allow.

Role of modelling and simulation: a European regulatory perspective

Modelling and simulation (M&S) of clinical data, e.g. pharmacokinetic, pharmacodynamic and clinical endpoints, is a useful approach for more efficient interpretation of collected data and for extrapolation of knowledge to the entire target population. This type of documentation is included in the majority of marketing authorization applications for new medicinal products. This article summarizes the current status of regulatory review with respect to the role of M&S in Europe from the perspective of the Swedish Medical Products Agency. At present, regulatory bodies in Europe encourage the application of the M&S approach during drug development. However, there is a lack of consensus and transparent guidance documents. The main regulatory usage is in the evaluation of dose choices in sub-populations and as support for the dosing regimen in general. The regulatory review of conestat alfa illustrates how the dose recommendation was revised during the approval procedure based on M&S information. A survey of marketing authorization applications for new medicinal products approved in 2010 revealed that the use of the information gained from M&S documentation varies with respect to both regulatory review and the applicants' presentation of the data in the submitted dossier. Increased utilization and broadened application of M&S is anticipated in pharmaceutical development, where one area of focus is medicines for paediatric patients. Accordingly, the regulatory agencies will need to increase their capability to assess and utilize this type of information, and an interactive process among regulatory agencies is warranted to provide more unified regulatory assessment and guidance. Moreover, applicants are encouraged to expand on the usage of exposure-response models to map the systemic exposure range that yields safe and efficacious treatment and to improve the presentation of the gained knowledge in summary documents of the marketing authorization applications.

Exposure-response relationship of AMG 386 in combination with weekly paclitaxel in recurrent ovarian cancer and its implication for dose selection

Purpose

To characterize exposure–response relationships of AMG 386 in a phase 2 study in advanced ovarian cancer for the facilitation of dose selection in future studies.

Methods

A population pharmacokinetic model of AMG 386 (N = 141) was developed and applied in an exposure–response analysis using data from patients (N = 160) with recurrent ovarian cancer who received paclitaxel plus AMG 386 (3 or 10 mg/kg once weekly) or placebo. Reduction in the risk of progression or death with increasing exposure (steady-state area under the concentration-versus-time curve [AUC_ss]) was assessed using Cox regression analyses. Confounding factors were tested in multivariate analysis. Alternative AMG 386 doses were explored with Monte Carlo simulations using population pharmacokinetic and parametric survival models.

Results

There was a trend toward increased PFS with increased AUC_ss (hazard ratio [HR] for each one-unit increment in AUC_ss, 0.97; P = 0.097), suggesting that the maximum effect on prolonging PFS was not achieved at the highest dose tested (10 mg/kg). Among patients with AUC_ss ≥ 9.6 mg h/mL, PFS was 8.1 months versus 5.7 months for AUC_ss < 9.6 mg h/mL and 4.6 months for placebo. No relationship between AUC_ss and grade ≥3 adverse events was observed. Simulations predicted that AMG 386 15 mg/kg once weekly would result in an AUC_ss ≥ 9.6 mg h/mL in >90% of patients with median PFS of 8.2 months versus 5.0 months for placebo (HR [15 mg/kg vs. placebo], 0.56).

Conclusions

Increased exposure to AMG 386 was associated with improved clinical outcomes in recurrent ovarian cancer, supporting the evaluation of a higher dose in future studies.

Electronic supplementary material

The online version of this article (doi:10.1007/s00280-011-1787-5) contains supplementary material, which is available to authorized users.

Pharmacometrics 2020

This special issue of the Journal of Clinical Pharmacology is dedicated to pharmacometrics, covering topics related to methodological research, application to decisions, standardization, PhRMA survey, and growth strategy. Innovative methodological and technological advances in analyzing disease, drug, and trial data have equipped pharmacometricians with the know-how to influence high-level decisions, which in turn creates more pharmacometric opportunities. Pharmacometrics is revolutionizing drug development and regulatory decision making. To sustain the success and growth of this field, we need to up the ante. Strategic goals for pharmacometric groups in industry, regulatory agencies, and academia are proposed in this report. These goals should be of significance to all stakeholders who have a vested interest in drug development and therapeutics. The future of pharmacometrics depends on how well we all can deliver on the strategic goals.

Model-based drug development survey finds pharmacometrics impacting decision making in the pharmaceutical industry

During the past decade, the pharmaceutical industry has seen the increasing application of pharmacometrics approaches in drug development. However, the full potential of incorporating model-based approaches in drug development and its impact on decision making has not been fully realized to date. In 2009, a survey on model-based drug development (MBDD) was conducted (1) to further understand the current state of MBDD in the pharmaceutical industry and (2) to identify opportunities to realize the full potential of MBDD. Ten large and mid-sized pharmaceutical companies provided responses to this survey. The results indicate that MBDD is achieving broad application in early and late development and is positively affecting both internal and regulatory decisions. Senior leadership (vice president and higher) within the companies indicated widely accepted utility for dose selection and gaining acceptance for study design and regulatory interactions but limited acceptance in discovery and commercial/pipeline decisions. Mounting appreciation for the impact of MBDD on internal and regulatory decision-making bodes well for the future of the pharmacometric discipline and the growth of opportunities to realize the full potential of MBDD.