Improving drug safety with a systems pharmacology approach.

Systems pharmacology is used to mechanistically analyze drug-adverse drug reaction (ADRs) pairs and is a promising solution to the complex problem of understanding mechanisms of toxicity. In this research, we have explored the feasibility of retrospectively mapping population-level adverse events from the FDA Adverse Event Reporting System (FAERS) to chemical and biological databases to identify drug safety signals and the underlying molecular mechanisms. We used an analytic platform - Molecular Analysis of Side Effects (MASE™). For this purpose, we selected the adverse event of severe and potentially fatal cutaneous reactions (SCARs) that are associated with acetaminophen (APAP). SCARs encompass the continuum between Stevens-Johnson Syndrome (SJS) and Toxic Epidermal Necrolysis (TEN). We found a statistically significant association between APAP and TEN, the most severe form of SCARs. We also explored the influence of APAP on other classes of drugs commonly associated with SCARs. We found that APAP significantly reduced the risk of SCARs commonly associated with carbamazepine (CBZ). We used molecular docking simulations to propose a mechanism for APAP's reduction in CBZ-induced SCARs which is competitive inhibition of the binding of CBZ to HLA-B*15:02. We conclude that systems pharmacology can complement established surveillance methodologies by providing a means to undertake an independent investigation and review of the mechanisms by which drugs cause adverse events.

[1]  Anne Elixhauser,et al.  Medication-Related Adverse Outcomes in U.S. Hospitals and Emergency Departments, 2008 , 2011 .

[2]  Yuan-Tsong Chen,et al.  Direct interaction between HLA-B and carbamazepine activates T cells in patients with Stevens-Johnson syndrome. , 2012, The Journal of allergy and clinical immunology.

[3]  C. Sotozono,et al.  In Silico Risk Assessment of HLA-A*02:06-Associated Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis Caused by Cold Medicine Ingredients , 2013, Journal of toxicology.

[4]  A. Grizzle,et al.  Drug-related morbidity and mortality: updating the cost-of-illness model. , 2001, Journal of the American Pharmaceutical Association.

[5]  M. Lindquist,et al.  A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions , 2002, Pharmacoepidemiology and drug safety.

[6]  Feixiong Cheng,et al.  Biomarker-based drug safety assessment in the age of systems pharmacology: from foundational to regulatory science. , 2015, Biomarkers in medicine.

[7]  Jie Shen,et al.  Prediction of human genes and diseases targeted by xenobiotics using predictive toxicogenomic-derived models (PTDMs). , 2013, Molecular bioSystems.

[8]  正博 頭金.  FDA adverse event reporting system (FAERS) , 2015 .

[9]  D. Margulies,et al.  Abacavir induces loading of novel self-peptides into HLA-B*57: 01 an autoimmune model for HLA-associated drug hypersensitivity , 2012, AIDS.

[10]  D. Bates,et al.  The Costs of Adverse Drug Events in Hospitalized Patients , 1997 .

[11]  Dieter Müller,et al.  Pathway analysis tools and toxicogenomics reference databases for risk assessment. , 2008, Pharmacogenomics.

[12]  A. Bate,et al.  Quantitative signal detection using spontaneous ADR reporting , 2009, Pharmacoepidemiology and drug safety.

[13]  D. Hunter,et al.  Valdecoxib: the rise and fall of a COX-2 inhibitor , 2013, Expert opinion on pharmacotherapy.

[14]  David W. Bates,et al.  The costs of adverse drug events in hospitalized patients. Adverse Drug Events Prevention Study Group , 1997 .

[15]  A. Flahault,et al.  Medications as Risk Factors of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Children: A Pooled Analysis , 2009, Pediatrics.

[16]  Yoshiro Saito,et al.  Pharmacogenomics of severe cutaneous adverse reactions and drug-induced liver injury , 2013, Journal of Human Genetics.

[17]  Jie Shen,et al.  Adverse Drug Events: Database Construction and in Silico Prediction , 2013, J. Chem. Inf. Model..

[18]  J. McCluskey,et al.  Immune self-reactivity triggered by drug-modified HLA-peptide repertoire , 2012, Nature.

[19]  R. O’Neill,et al.  Use of Screening Algorithms and Computer Systems to Efficiently Signal Higher-Than-Expected Combinations of Drugs and Events in the US FDA’s Spontaneous Reports Database , 2002, Drug safety.

[20]  P. Bork,et al.  Systematic identification of proteins that elicit drug side effects , 2013, Molecular systems biology.

[21]  Russ B. Altman,et al.  A novel signal detection algorithm for identifying hidden drug-drug interactions in adverse event reports , 2012, J. Am. Medical Informatics Assoc..

[22]  D. Becker.  Toxic epidermal necrolysis , 1969, The Lancet.

[23]  T. Profaizer,et al.  HLA alleles and drug hypersensitivity reactions , 2012, International journal of immunogenetics.

[24]  Zhongming Zhao,et al.  Machine learning-based prediction of drug-drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties. , 2014, Journal of the American Medical Informatics Association : JAMIA.

[25]  R. Cairoli,et al.  A study of HLA class I and class II 4‐digit allele level in Stevens–Johnson syndrome and toxic epidermal necrolysis , 2011, International journal of immunogenetics.

[26]  Manfred Hauben,et al.  Potential Use of Data-Mining Algorithms for the Detection of ‘Surprise’ Adverse Drug Reactions , 2007, Drug safety.

[27]  M. Mockenhaupt.  Severe drug‐induced skin reactions: clinical pattern, diagnostics and therapy , 2009, Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG.

[28]  L. Naldi,et al.  Stevens-Johnson syndrome and toxic epidermal necrolysis: assessment of medication risks with emphasis on recently marketed drugs. The EuroSCAR-study. , 2008, The Journal of investigative dermatology.

[29]  L. Naldi,et al.  Nevirapine and the risk of Stevens–Johnson syndrome or toxic epidermal necrolysis , 2001, AIDS.

[30]  S. Mallal,et al.  Drug hypersensitivity: pharmacogenetics and clinical syndromes. , 2011, The Journal of allergy and clinical immunology.

[31]  W. DuMouchel,et al.  Novel Statistical Tools for Monitoring the Safety of Marketed Drugs , 2007, Clinical pharmacology and therapeutics.

[32]  U. Sarkar,et al.  Adverse drug events in U.S. adult ambulatory medical care. , 2011, Health services research.

[33]  M. Hauben,et al.  Data mining for signals in spontaneous reporting databases: proceed with caution , 2007, Pharmacoepidemiology and drug safety.