Impact of pharmacokinetic-pharmacodynamic modelling in early clinical drug development

Training the next generation of pharmacometric modelers: a multisector perspective

The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.

Antiprotozoal agents: How have they changed over a decade?

Neglected tropical diseases are a diverse group of communicable diseases that are endemic in low- or low-to-middle-income countries located in tropical and subtropical zones. The number and availability of drugs for treating these diseases are low, the administration route is inconvenient in some cases, and most of them have safety, efficacy, or adverse/toxic reaction issues. The need for developing new drugs to deal with these issues is clear, but one of the most drastic consequences of this negligence is the lack of interest in the research and development of new therapeutic options among major pharmaceutical companies. Positive changes have been achieved over the last few years, although the overall situation remains alarming. After more than one decade since the original work reviewing antiprotozoal agents came to light, now it is time to question ourselves: How has the scenario for the treatment of protozoal diseases such as malaria, leishmaniasis, human African trypanosomiasis, and American trypanosomiasis changed? This review covers the last decade in terms of the drugs currently available for the treatment of these diseases as well as the clinical candidates being currently investigated.

The Case for an Unblinded Modeler in Early Clinical Development

The current trend for clinical pharmacology is toward more complex studies (eg, umbrella protocols covering single and multiple ascending doses, food effect, metabolism pathways), requiring many decisions to be made during their conduct. This article discusses guidance of such early clinical studies by modeling and simulation. The ability to make use of all available information each time new data become available during the study requires the modeling scientist to be unblinded. This must of course not jeopardize the blinding of the clinical team, and this article discusses how unblinding can be prevented. Although modeling and simulation are established for guidance of the drug development process overall, they are not frequently used for guidance on a small scale, that is, during studies with the largest uncertainty, the first-in-human studies. Application of a quantitative model backbone makes early clinical drug development a more efficient process and provides additional safety for healthy subjects and patients. Real clinical impact is illustrated by 3 case studies that show different contributions from unblinded modeling: dose escalation based on safety data, modeling and predicting with explicit incorporation of in vitro data, and dose escalation supported by unblinded analysis of adverse event data, which resulted in new insights of the clinical team without being unblinded and made it possible to proceed with dose escalation and to extend the study with an up-titration group.