From Real-World Patient Data to Individualized Treatment Effects Using Machine Learning: Current and Future Methods to Address Underlying Challenges.

Clinical decision making needs to be supported by evidence that treatments are beneficial to individual patients. Although randomized control trials (RCTs) are the gold standard for testing and introducing new drugs, due to the focus on specific questions with respect to establishing efficacy and safety vs. standard treatment, they do not provide a full characterization of the heterogeneity in the final intended treatment population.

Percutaneous coronary intervention still not accessible for many South Africans.

Introduction: The incidence of myocardial infarction is rising in Sub-Saharan Africa. In order to reduce mortality, timely reperfusion by percutaneous coronary intervention (PCI) or thrombolysis followed by PCI is required. South Africa has historically been characterised by inequities in healthcare access based on geographic and socioeconomic status.

Drug-disease modeling in the pharmaceutical industry - where mechanistic systems pharmacology and statistical pharmacometrics meet.

Modeling & simulation (M&S) methodologies are established quantitative tools, which have proven to be useful in supporting the research, development (R&D), regulatory approval, and marketing of novel therapeutics. Applications of M&S help design efficient studies and interpret their results in context of all available data and knowledge to enable effective decision-making during the R&D process. In this mini-review, we focus on two sets of modeling approaches: population-based models, which are well-established within the pharmaceutical industry today, and fall under the discipline of clinical pharmacometrics (PMX); and systems dynamics models, which encompass a range of models of (patho-)physiology amenable to pharmacological intervention, of signaling pathways in biology, and of substance distribution in the body (today known as physiologically-based pharmacokinetic models) - which today may be collectively referred to as quantitative systems pharmacology models (QSP).

Managing the Risk of CYP3A Induction in Drug Development: A Strategic Approach.

Induction of cytochrome P450 (P450) can impact the efficacy and safety of drug molecules upon multiple dosing with coadministered drugs. This strategy is focused on CYP3A since the majority of clinically relevant cases of P450 induction are related to these enzymes. However, the in vitro evaluation of induction is applicable to other P450 enzymes; however, the in vivo relevance cannot be assessed because the scarcity of relevant clinical data.

Managing the challenge of chemically reactive metabolites in drug development.

The normal metabolism of drugs can generate metabolites that have intrinsic chemical reactivity towards cellular molecules, and therefore have the potential to alter biological function and initiate serious adverse drug reactions. Here, we present an assessment of the current approaches used for the evaluation of chemically reactive metabolites. We also describe how these approaches are being used within the pharmaceutical industry to assess and minimize the potential of drug candidates to cause toxicity.

Acyl glucuronides: the good, the bad and the ugly.

Acyl glucuronidation is the major metabolic conjugation reaction of most carboxylic acid drugs in mammals. The physiological consequences of this biotransformation have been investigated incompletely but include effects on drug metabolism, protein binding, distribution and clearance that impact upon pharmacological and toxicological outcomes. In marked contrast, the exceptional but widely disparate chemical reactivity of acyl glucuronides has attracted far greater attention.