A Sampling of DARS Projects
Biomedical and Chemical Informatics
Application of in silico (computational) approaches can speed drug development by enabling pharmaceutical applicants to apply predictive models early in development and for regulators to perform rapid analyses in the premarket or postmarket phase. DARS develops and validates chemical and biomedical informatics tools and models for these applications.
Adverse Event Profiling
DARS utilizes target-adverse event profiles to predict adverse events. DARS researchers utilize adverse event data from the FDA Adverse Event Reporting System, FDA drug labels, and peer-reviewed literature and databases containing drug and target information to connect adverse events to drug targets.
Modeling to Inform Scheduling of Novel Substances of Abuse Potential
DARS develops computational models to help determine whether chemical substances are a risk to public safety and should be temporarily placed into Schedule I of the Controlled Substances Act (CSA) (21 U.S.C. 811 (h)). Computational methods that can be rapidly deployed are urgently needed to assess the public health risk of newly synthesized street drugs as manufacturers make minor modifications to existing scheduled substances to avoid prosecution.
Chemical Structure-Activity Relationship Modeling
DARS chemical informatics projects (using computational techniques to solve chemistry problems) are focused on endpoints of regulatory interest, linked through chemical structure. Research activities include (1) database development for model training and validation; (2) development of web-based applications to enable direct structure-based searching by CDER staff; and (3) (Q)SAR model development (models using physical and chemical properties to predict the behavior of new drugs) to support drug safety review. Databases and models are used to respond to regulatory review consultation requests.
1. Sarntivijai S, Zhang S, Jagannathan DG, Zaman S, Burkhart KK, Omenn GS, He Y, Athey BD, Abernethy DR. Linking MedDRA((R))-Coded Clinical Phenotypes to Biological Mechanisms by the Ontology of Adverse Events: A Pilot Study on Tyrosine Kinase Inhibitors. Drug Saf. 2016;39(7):697-707. PMID: 27003817
2. Zhu X, Kruhlak NL. Construction and analysis of a human hepatotoxicity database suitable for QSAR modeling using post-market safety data. Toxicology. 2014;321:62-72. PMID: 24721472
3. Kruhlak NL, Benz RD, Zhou H, Colatsky TJ. (Q)SAR modeling and safety assessment in regulatory review. Clin Pharmacol Ther. 2012;91(3):529-34. PMID: 22258468
4. Ahlberg E, Amberg A, Beilke LD, Bower D, Cross KP, Custer L, Ford KA, Van Gompel J, Harvey J, Honma M, Jolly R, Joossens E, et al. Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity. Regul Toxicol Pharmacol. 2016;77:1-12. PMID: 26879463
5. Duggirala HJ, Tonning JM, Smith E, Bright RA, Baker JD, Ball R, Bell C, Bright-Ponte SJ, Botsis T, Bouri K, Boyer M, Burkhart K, et al. Use of data mining at the Food and Drug Administration. J Am Med Inform Assoc. 2016;23(2):428-34. PMID: 26209436
Tissue Based Biomarkers and Digital Quantification of Injury
Biomarkers are defined characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathologic processes, or biological responses to a therapeutic intervention. Biomarkers can be used to select patients for clinical trials and treatment, identify safety problems related to a drug, or reveal pharmacological activity predictive of therapeutic response. DARS scientists have contributed to the development, characterization, and validation of multiple biomarkers and have been involved in the review of biomarker qualification packages submitted to the Agency.
MicroRNAs (an RNA molecule that does not make protein) can act as biomarkers for acute pancreatic injury. When cells are injured, the microRNAs are released from the cell into the blood. From a blood sample, the microRNAs can be detected, indicating that injury has occurred. More information can be found in the Spotlight on CDER Science.
Histopathology studies (examination of tissue to study disease) can vary widely in industry. DARS evaluated different methods and determined that more complex evaluation methods did not outperform the existing standard methodology. Ultimately, FDA published the Guidance to Industry on Histopathology Methods for Biomarker Qualifications Studies that aligned with and was supported by DARS data.
1. Zhang L, Zhang J, Shea K, Xu L, Tobin G, Knapton A, Sharron S, Rouse R. Autophagy in pancreatic acinar cells in caerulein-treated mice: immunolocalization of related proteins and their potential as markers of pancreatitis. Toxicol Pathol. 2014;42(2):435-57. PMID: 23640381
2. Rouse R RB, Thompson K. Circulating microRNAs as Biomarkers of Drug-Induced Pancreatitis. In: Sahu SC, editor. microRNAs in Toxicology and Medicine: Wiley; 2013. p. 425-36. Link
3. Shea K, Stewart S, Rouse R. Assessment standards: comparing histopathology, digital image analysis, and stereology for early detection of experimental cisplatin-induced kidney injury in rats. Toxicol Pathol. 2014;42(6):1004-15. PMID: 24201815
4. Goodwin D, Rosenzweig B, Zhang J, Xu L, Stewart S, Thompson K, Rouse R. Evaluation of miR-216a and miR-217 as potential biomarkers of acute pancreatic injury in rats and mice. Biomarkers. 2014;19(6):517-29. PMID: 25059555
5. Rouse R, Rosenzweig B, Shea K, Knapton A, Stewart S, Xu L, Chockalingam A, Zadrozny L, Thompson K. MicroRNA biomarkers of pancreatic injury in a canine model. Exp Toxicol Pathol. 2017;69(1):33-43. PMID: 27866884
Drug Transporters and Metabolism
DARS uses in vitro microsomal assays to establish a new drug as an inhibitor or non-inhibitor of the P450 enzyme, which can affect drug levels in the body and lead to drug interactions. Additionally, DARS utilizes in vitro efflux assays to establish a drug as an inhibitor or substrate (a compound that interacts with a transporter or enzyme) of a drug transporter.
1. Volpe DA. Transporter assays as useful in vitro tools in drug discovery and development. Expert Opin Drug Discov. 2016;11(1):91-103. PMID: 26512742
2. Hartman N, Zhou H, Mao J, Mans D, Boyne M, 2nd, Patel V, Colatsky T. Characterization of the methemoglobin forming metabolites of benzocaine and lidocaine. Xenobiotica. 2017;47(5):431-8. PMID: 27321253
3. Hartman NR, Mao JJ, Zhou H, Boyne MT, 2nd, Wasserman AM, Taylor K, Racoosin JA, Patel V, Colatsky T. More methemoglobin is produced by benzocaine treatment than lidocaine treatment in human in vitro systems. Regul Toxicol Pharmacol. 2014;70(1):182-8. PMID: 25010377
4. Brouwer KR FS, Lai Y, Luo G, Roe AL, Volpe DA, Yang K. The Importance of In Vitro Liver Models: Experts Discuss Whole-Cell Systems, Transporter Function, and the Best Models for Future In Vitro Testing. Applied In Vitro Toxicology. 2016;2(1). Link
Comprehensive in vitro Proarrhythmia Assay (CiPA)
DARS is working with an international consortium on the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative, which is developing an in vitro (cellular models) and in silico (computational) paradigm for cardiac safety evaluation of new drugs. CiPA involves 4 components: (1) in vitro assessment of drug effects on multiple cardiac ion channels; (2) integration of the multi-ion channel effects in an in silico computer model of the human ventricular cardiomyocyte (heart cells) to output a proarrhythmic (abnormal heart rhythm) risk score; (3) assessment for unanticipated effects in vitro using human-induced pluripotent stem cell-derived cardiomyocytes; and (4) phase 1 clinical studies with exposure-response analysis. DARS is leading applied research across all 4 components to develop and validate this novel regulatory paradigm.
1. Li Z, Dutta S, Sheng J, Tran PN, Wu W, Chang K, Mdluli T, Strauss DG, Colatsky T. Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-a-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology. Circ Arrhythm Electrophysiol. 2017;10(2):e004628. PMID: 28202629
2. Ribeiro AJ, Ang YS, Fu JD, Rivas RN, Mohamed TM, Higgs GC, Srivastava D, Pruitt BL. Contractility of single cardiomyocytes differentiated from pluripotent stem cells depends on physiological shape and substrate stiffness. Proc Natl Acad Sci U S A. 2015;112(41):12705-10. PMID: 26417073
3. Strauss DG, Vicente J, Johannesen L, Blinova K, Mason JW, Weeke P, Behr ER, Roden DM, Woosley R, Kosova G, Rosenberg MA, Newton-Cheh C. Common Genetic Variant Risk Score Is Associated With Drug-Induced QT Prolongation and Torsade de Pointes Risk: A Pilot Study. Circulation. 2017;135(14):1300-10. PMID: 28213480
4. Vicente J, Johannesen L, Hosseini M, Mason JW, Sager PT, Pueyo E, Strauss DG. Electrocardiographic Biomarkers for Detection of Drug-Induced Late Sodium Current Block. PLoS One. 2016;11(12):e0163619. PMID: 28036334
5. Strauss DG, Blinova K. Clinical Trials in a Dish. Trends Pharmacol Sci. 2017;38(1):4-7. PMID: 27876286