Use of “Omics” Technologies for Mechanistic Understandings of Toxicological Events

1. 6th International Conference and Exhibition on Analytical & Bioanalytical Techniques @Valencia, Spain, Sep. 1-3, 2015 Use of “Omics” Technologies for Mechanistic Understandings of Toxicological Events Toshinori Yamamoto, Ph.D. Vice President and Head of Preclinical Research RaQualia Pharma Inc. 1-21-19, Meieki Minami, Nakamura-ku, Nagoya, Aichi 450-0003, Japan

2. Introduction • In Pharmaceutical Industries, “drug toxicity” findings which are observed in animal studies as well as clinical trials sometimes lead to “discontinuation” of drug candidates • To minimize the risk of “discontinuations” (attrition improvement), understandings of the phenomena/backgrounds surrounding toxicological events occurred must be a key element in R&D of new chemical entities (NCEs) • Often requiring mechanistic investigations to understand toxicological mechanism of actions and then to make “Go” or “No go” decisions of the compounds • In the post-genomic era, “Omics” technologies were introduced and has been rapidly increasing utilization in toxicology field • prefix of “toxico-” added to each omics technology; toxicogenomics, toxicoproteomics, toxicometabolomics, etc. • The objectives of toxicometabolomics are to identify and characterize the both endogenous and exogenous metabolites which are the end products of cellular metabolism and drug metabolism, respectively • Toxicometabolomics enables to capture the phenotypic changes in the events, which are generated by enzymatic proteins as resultants of gene expression, at the molecular level; therefore, smooth “Translation” of the findings can be made into the clinic as “potential biomarkers”

3. Objective of Today’s Talk Today, I will review the usefulness of toxicometabolomics technologies, and other toxic-Omics technologies • Nuclear magnetic resonance [NMR]-based • Mass spectrometry [MS]-based • Others Furthermore, newly introduced technology, imaging MS (IMS) is considered applicable in the toxicology field, hence its toxicological usability will be also reviewed

4. Drug R&D Process ~ From Discovery, Preclinical, Clinical to then Approval ~ 11 million compounds Screened 1 FDA approved drug A few leads for each target Amount of time, on average, for a successful new drug to move through and complete the four stages. Abbreviations IND: Investigational New Drug Application NDA: New Drug Application Success Rate: 1/11,000,000 Modifies from “New Drug Development, GAO-07-49, November, 2006” and “Drug development Science - Obstacles and opportunities for collaboration among academia, industry and government, 2005”

5. Major Reasons for the Discontinuation in Drug R&D • In the year 2000, toxicity and lack of clinical safety accounted for ~30% of the failed drug development programs (a) • Safety issues remain a significant hurdle even in the late development stages of Phase 2 and Phase 3, and after submission (b, c) • Adverse drug reactions are the cause of the majority of “Withdrawals”, “Restricted use ” or “Black-box warnings” issued by regulatory agencies, and even rank highly as a cause of disease and death Hornberg JJ et al., Drug Discovery Today, 2014

6. Impact and Frequency of Different Toxicities Throughout the Pharmaceutical Life Cycle • Lack of early detection of safety signals • Lack of detection of safety hazards preclinically • Lack of confidence/knowledge/precision in preclinical-clinical translation Redfern WS et al., The Toxicologist, 2010

7. Time-Scales of “Omics” Events Stimulation Toxicity Sampling points Protein mRNA a) b) c) d) DNA Genes Proteins mRNA Level Signal Protein Level Metabolite Changes in foci Cell Damage Metabolites Stimulation Toxicogenomics Toxicoproteomics Recovery Regenerative / degenerative changes Primary changes Damage/Toxicity Index Time Dosing Modified from Nicholson et al., Nature Review Drug Discovery, 2002

8. “Omics” Space Safety Biomarkers Safety Biomarkers Binding Safety Biomarkers Safety Biomarkers Transcription Safety Biomarkers Macroscopic Physiology, Disease, Pathology, Toxicity … Systems Biology/Toxicology Phenomics Metabonomics Proteomics Transcriptomics Genomics Microscopic Modified from Toyoda and Wada, Bioinformatics, 2004

9. Metabolomics • Only tool providing the information about the connections between the expression of genes and proteins, and the external environments • Exclusively based on small molecules found in any living cells, organs or organisms, and the physiological effects (changes) of these small molecule metabolites • Give us the “Exact Picture” of the cellular activity and surrounding environments, which is correlating with phenotypes, “Phenomics” Kumar B et al., Pharmacol. Rep., 2014

10. Examples • Example #1: Testicular Metabolomics • Nuclear Magnetic Resonance (NMR) • Example #2: Saliva Metabolomics • Capillary electrophoresis coupled with time-of-flight mass spectrometry(CE-TOF-MS) • Example #3: Further approach • MALDI Mass Spectrometry

11. Example #1: Testicular Metabolomics Control • Purposes • Investigate the toxicological effects of ethylene glycol monomethyl ether (EGME), a well-known spermatocytes toxicant, on male reproductive organs by analysis of intact testicular tissues ex vivo • Platform: • High-resolution Magic Angle Spinning (Hr-MAS) 1H-NMR spectroscopy (600 MHz) • Other Measurements: • Body and Reproductive organs weight, Plasma biochemistry and Histopathology EGME, 50 mg/kg EGME, 2000 mg/kg Red arrow: degenerative changes in spermatocytes Yamamoto T. et al., J. Toxicol. Sci, 2007

12. Example #1: Testicular Metabolomics 8 10 6 4 5 2 0 t[2] 0 t[2] -2 -5 -4 -6 -10 -8 -10 0 10 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 t[1] t[1] Control Low-dose 4.0 3.5 3.0 2.5 2.0 1.5 1.0 4.0 3.5 3.0 2.5 2.0 1.5 1.0 Chemical Shift (ppm) Chemical Shift (ppm) lipid High-dose Yamamoto T. et al., J. Toxicol. Sci, 2007 Testis phosphatidylcholine Control PCA GSH GSH High phosphocholine Control Low-dose lactate creatine Low lysine High-dose alanine acetate Caput Epididymis PCA Control High Low

13. Example #1: Testicular Metabolomics 6 4 4 2 2 0 0 t[2] t[2] -2 -2 -4 -4 -6 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 t[1] t[1] Yamamoto T. et al., J. Toxicol. Sci, 2007 Urine PCA PCA Low Control or Pre-dose High, 8-24 hr High, 0-8 hr Plasma Control or Pre-dose Low High, 24 hr High, 6 hr

14. Example #1: Testicular Metabolomics • Testicular toxicity induced by EGME resulted from … • Perturbation of the energy supply process • Lactate, and others • Suppression of the TCA cycle • 2-oxoglutarate, citrate, succinate, ketone-bodies, acetoacetate, β-hydroxybutyrate, etc. • Oxidative stress • GSH -------------------------------------------------------------------------------------------------------------------------------- • Integrated analyses of intact tissues and biofluids using 1H-NMR provides a more detailed knowledge in in vivo molecular events • Metabolomics enable to investigate whether a target organs in normal or damaged, before histopathological changes occurred. Candidates of Safety Biomarker

15. Example #2: Saliva Metabolomics • Background: • Saliva is a readily accessible and informative biofluid • Making it ideal for the early detection of a wide range of diseases including CV, renal, and autoimmune, viral and bacterial infections and cancers, etc. • Metabolomics technology might be suitable for Saliva-based diagnostics, then offers a promising clinical strategy, characterizing the association between salivary analytes and a particular disease • Purposes: • In order to obtain and compare comprehensive salivary metabolic profiles of patients with oral, breast or pancreatic cancers, and identify individual cancer-specific markers in cancer diagnosis • Platform: • Capillary electrophoresis coupled with time-of-flight mass spectrometry (CE-TOF-MS)

16. Example #2: Saliva Metabolomics Blue: Control (n=87) Red: Oral cancer (n=69) Sugimoto M. et al., Metabolomics, 2010

17. Example #2: Saliva Metabolomics • Heat map has clearly distinguished the diseases by showing the different metabolites levels in saliva, suggesting that cancer-specific signatures were embedded in saliva metabolites • The metabolites identified may be promising biomarkers for medical screening Breast Cancer Pancreatic Cancer Periodontal Disease Control Oral Cancer Metabolites Individuals Sugimoto M. et al., Metabolomics, 2010

18. Example #3: Imaging Mass Spectrometry (IMS) Publication in IMS IMS Molecular Targets in IMS Proteins Lipids Metabolites Drugs/Xenobiotics Inorganics Other Compound Adapted from presentation slide by BrukerDaltonics (2015)

19. Example #3: Imaging Mass Spectrometry (IMS) Histopathology Procedure Uzbekova S. et al., Biology, 2015

20. Example #3: Imaging Mass Spectrometry (IMS) Whole Body Autoradiography Procedure Stoeckli M. et al., Int. J. Mass Spectom, 2007

21. Example #3: Imaging Mass Spectrometry (IMS) • Application in Toxicology Fields: • In situ Mass Spectrometry Imaging and Ex Vivo Characterization of Renal Crystalline Deposits Induced in Multiple Preclinical Drug Toxicity Studies Nilsson A. et al., PLOS ONE, 2012 • A New Safety Concern for Glaucoma Treatment Demonstrated by Mass Spectrometry Imaging of Benzalkonium Chloride Distribution in the Eye, an Experimental Study in Rabbits Brignole-Baudouin F. et al., PLOS ONE, 2012 • Central Nervous System Disposition and Metabolism of Fosdevirine (GSK2248761), a Non-Nucleoside Reverse Transcriptase Inhibitor: An LC-MS and Matrix-Assisted Laser Desorption/Ionization Imaging MS Investigation into Central Nervous System Toxicity Castellino S. et al., Chem. Res. Toxicol., 2013 • A Comparative Study of Hollow Copper Sulfide Nanoparticles and Hollow Gold Nanospheres on Degradability and Toxicity Guo L. et al., ACS Nano, 2013

22. Concept Diagram of Adverse Outcome Pathway (AOP) • Adverse Outcome Pathway (AOP) is a conceptual construct that portrays existing knowledge concerning the linkage between a direct “molecular initiating event” and an “adverse outcome (AO)” at a biological level of organization relevant to risk assessment • Each AOP begins with a molecular initiating event in which a chemical interacts with a biological target (Anchor 1) leading to a sequential series of higher order effects to produce an AO with direct relevance to a given risk assessment context (Anchor 2) • AOPs are generally a sequential series of events that, by definition, span multiple levels of biological organization Ankley DT et al., Environ. Toxicol. Chem., 2010

23. Concluding Remarks • Not surprisingly, “toxic-omics” techniques including toxicometabolomics are becoming much more important in the toxicology fields • Appropriate use of toxic-omics technologies enables us to understand the comprehensive mechanisms of toxicity • The biomarkers, which are identified with toxicometabolomics, normally reflect pathophysiological events expected macroscopically, and also must be easily translated into the clinical fields

24. Thank you so much for your attention