Adverse drug reactions and pharmacogenomics: recent advances

Statistical assessment of biomarker replicability using MAJAR method

In the era of precision medicine, many biomarkers have been discovered to be associated with drug efficacy and safety responses, which can be used for patient stratification and drug response prediction. Due to the small sample size and limited power of randomized clinical studies, meta-analysis is usually conducted to aggregate all available studies to maximize the power for identifying prognostic and predictive biomarkers. However, it is often challenging to find an independent study to replicate the discoveries from the meta-analysis (e.g. meta-analysis of pharmacogenomics genome-wide association studies (PGx GWAS)), which seriously limits the potential impacts of the discovered biomarkers. To overcome this challenge, we develop a novel statistical framework, MAJAR (meta-analysis of joint effect associations for biomarker replicability assessment), to jointly test prognostic and predictive effects and assess the replicability of identified biomarkers by implementing an enhanced expectation-maximization algorithm and calculating their posterior-probability-of-replicabilities and Bayesian false discovery rates (Fdr). Extensive simulation studies were conducted to compare the performance of MAJAR and existing methods in terms of Fdr, power, and computational efficiency. The simulation results showed improved statistical power with well-controlled Fdr of MAJAR over existing methods and robustness to outliers under different data generation processes. We further demonstrated the advantages of MAJAR over existing methods by applying MAJAR to the PGx GWAS summary statistics data from a large cardiovascular randomized clinical trial. Compared to testing main effects only, MAJAR identified 12 novel variants associated with the treatment-related low-density lipoprotein cholesterol reduction from baseline.

Using human genetics to improve safety assessment of therapeutics

Human genetics research has discovered thousands of proteins associated with complex and rare diseases. Genome-wide association studies (GWAS) and studies of Mendelian disease have resulted in an increased understanding of the role of gene function and regulation in human conditions. Although the application of human genetics has been explored primarily as a method to identify potential drug targets and support their relevance to disease in humans, there is increasing interest in using genetic data to identify potential safety liabilities of modulating a given target. Human genetic variants can be used as a model to anticipate the effect of lifelong modulation of therapeutic targets and identify the potential risk for on-target adverse events. This approach is particularly useful for non-clinical safety evaluation of novel therapeutics that lack pharmacologically relevant animal models and can contribute to the intrinsic safety profile of a drug target. This Review illustrates applications of human genetics to safety studies during drug discovery and development, including assessing the potential for on- and off-target associated adverse events, carcinogenicity risk assessment, and guiding translational safety study designs and monitoring strategies. A summary of available human genetic resources and recommended best practices is provided. The challenges and future perspectives of translating human genetic information to identify risks for potential drug effects in preclinical and clinical development are discussed.

Predicting adverse drug reactions using publicly available PubChem BioAssay data

Adverse drug reactions (ADRs) can have severe consequences, and therefore the ability to predict ADRs prior to market introduction of a drug is desirable. Computational approaches applied to preclinical data could be one way to inform drug labeling and marketing with respect to potential ADRs. Based on the premise that some of the molecular actors of ADRs involve interactions that are detectable in large, and increasingly public, compound screening campaigns, we generated logistic regression models that correlate postmarketing ADRs with screening data from the PubChem BioAssay database. These models analyze ADRs at the level of organ systems, using the system organ classes (SOCs). Of the 19 SOCs under consideration, nine were found to be significantly correlated with preclinical screening data. With regard to six of the eight established drugs for which we could retropredict SOC-specific ADRs, prior knowledge was found that supports these predictions. We conclude this paper by predicting that SOC-specific ADRs will be associated with three unapproved or recently introduced drugs.

Risk assessment and mitigation strategies for reactive metabolites in drug discovery and development

Drug toxicity is a leading cause of attrition of candidate drugs during drug development as well as of withdrawal of drugs post-licensing due to adverse drug reactions in man. These adverse drug reactions cause a broad range of clinically severe conditions including both highly reproducible and dose dependent toxicities as well as relatively infrequent and idiosyncratic adverse events. The underlying risk factors can be split into two groups: (1) drug-related and (2) patient-related. The drug-related risk factors include metabolic factors that determine the propensity of a molecule to form toxic reactive metabolites (RMs), and the RM and non-RM mediated mechanisms which cause cell and tissue injury. Patient related risk factors may vary markedly between individuals, and encompass genetic and non-genetic processes, e.g. environmental, that influence the disposition of drugs and their metabolites, the nature of the adverse responses elicited and the resulting biological consequences. We describe a new strategy, which builds upon the strategies used currently within numerous pharmaceutical companies to avoid and minimize RM formation during drug discovery, and that is intended to reduce the likelihood that candidate drugs will cause toxicity in the human population. The new strategy addresses drug-related safety hazards, but not patient-related risk factors. A common target organ of toxicity is the liver and to decrease the likelihood that candidate drugs will cause liver toxicity (both non-idiosyncratic and idiosyncratic), we propose use of an in vitro Hepatic Liability Panel alongside in vitro methods for the detection of RMs. This will enable design and selection of compounds in discovery that have reduced propensity to cause liver toxicity. In vitro Hepatic Liability is assessed using toxicity assays that quantify: CYP 450 dependent and CYP 450 independent cell toxicity; mitochondrial impairment; and inhibition of the Bile Salt Export Pump. Prior to progression into development, a Hepatotoxicity Hazard Matrix combines data from the Hepatic Liability Panel with the Estimated RM Body Burden. The latter is defined as the level of covalent binding of radiolabelled drug to human hepatocyte proteins in vitro adjusted for the predicted human dose. We exemplify the potential value of this approach by consideration of the thiazolidinedione class of drugs.

Breath biomarkers for personalized medicine

Personalized medicine, in the near future, has the potential to revolutionize healthcare by allowing physicians to individualize therapy for patients through the early diagnosis of disease and risk assessment to optimize clinical response with minimal toxicity. The identification of biomarkers could detect, diagnose and help guide therapy to improve survival and quality of life by the early identification of responders to the drugs. Volatile organic compounds and stable isotope-labeled 13CO2 in breath can be uniquely utilized as in vivo diagnostic biomarkers of disease and/or lack of enzyme activity to aid physicians to personalize medication. Noninvasive detection of ailments and monitoring therapy by human breath analysis is an emerging field of medical diagnostics representing a rapid, economic and simple alternative to standard invasive blood analysis, endoscopy or harmful imaging techniques such as x-ray and CT scans.

Pharmacogenetics of idiosyncratic adverse drug reactions

Idiosyncratic adverse drug reactions are unpredictable and thought to have an underlying genetic etiology. With the completion of the human genome and HapMap projects, together with the rapid advances in genotyping technologies, we have unprecedented capabilities in identifying genetic predisposing factors for these relatively rare, but serious, reactions. The main roadblock to this is the lack of sufficient numbers of well-characterized samples from patients with such reactions. This is now beginning to be solved through the formation of international consortia, including developing novel ways of identifying and recruiting patients affected by these reactions, both prospectively and retrospectively. This has been led by the research on abacavir hypersensitivity - its association with HLA-B*5701 forms the gold standard of how we need to identify associations and implement them in clinical practice. Strong genetic predisposing factors have also been identified for hypersensitivity reactions such as are associated with carbamazepine, allopurinol, flucloxacillin, and statin-induced myopathy. However, for most other idiosyncratic adverse drug reactions, the genetic effect sizes have been low to moderate, although this may partly be due to the fact that only small numbers have been investigated and limited genotyping strategies have been utilized. It may also indicate that genetic predisposition will be dependent on multiple genes, with complex interactions with environmental factors. Irrespective of the strength of the genetic associations identified with individual idiosyncratic adverse drug reactions, it is important to undertake functional investigations to provide insights into the mechanism(s) of how the drug interacts with the gene variant to lead to a phenotype, which can take a multitude of clinical forms with variable severity. Such investigations will be essential in preventing the burden caused by idiosyncratic reactions, both in healthcare and in industry.

Generics: need for clinical concern?

The market of generic drugs is in continuous development in all countries, including Belgium. Their low cost explains their success in western and developed countries. However, clinical concerns have been raised when generics are used. Indeed, various studies suggest that generic substitution can be associated with reduced efficacy or (and) increased side-effects, particularly with drugs used in severe diseases or pathological states such as epilepsy, cardiac arrhythmia, prevention of graft-rejection, ... The generic drugs must have systemic bioavailability similar to that of the original drug. Thus, they have supposed similar therapeutic bioequivalence. However, similar pharmacokinetics does not imply identical therapeutic activity, particularly with drugs having narrow therapeutic indices such as anti-epileptics, anti-arrythmics ... In this case, switchability rather than prescribability may cause problems. Low pharmaceutical quality is more frequent when drugs are produced in certain countries, in some cases causing a real concern when activity and safety are considered.

Human drug hepatotoxicity: a contemporary clinical perspective

BACKGROUND

Drug-induced liver injury (DILI) constitutes a significant medical challenge. The rising number of marketed drugs, aging population and polypharmacy make it imperative to understand the clinical presentation of DILI and the processes used in the assessment of causality and early detection.

OBJECTIVE

This article reviews the current clinical understanding of DILI including presentation patterns, causality assessment, risk factor ascertainment and early detection strategies including liver test monitoring. Significant initiatives such as the Drug-Induced Liver Injury Network (DILIN) are also discussed.

METHODS

A narrative review of clinical studies of DILI, with emphasis on clinical features, causality and surveillance.

CONCLUSION

DILI remains a serious challenge in contemporary clinical practice. Further research and collaboration in the areas of epidemiology, causality and early detection are required to enhance the diagnosis and management of DILI.