Slide 1: mee Quantitative ae ae poiggiooy aL:
mee Quantitative ae ae poiggiooy aL: bo CS ty ‘ ester School ols eli 6
Slide 2: Disclosure
Disclosure I chair the scientific advisory committee for the DILI-sim Initiative and have a financial interest in the success of DILIsym Services Inc. 2
Slide 3: Reasons for Termination of Programs due to Safety by Organ System
Reasons for Termination of Programs due to Safety by Organ System (Astra Zeneca Experience) 3
Slide 4: Outline of Talk
Outline of Talk 1). Problem of liver safety 2). Current process to assess the safety of new drug candidates 3). Progress in QST modeling – DILIsym® 4). Conclusions
Slide 5: Outline of Talk
Outline of Talk 1). Problem of liver safety 2). Current process to assess the safety of new drug candidates 3). Progress in QST modeling – DILIsym/Renasym 4). Conclusions
Slide 6: Progress?
Progress? No drugs approved in the last decade have been withdrawn from the market in the U.S. due to liver safety concerns: 1). Drug developers and regulators and are smarter but 2). Clinical trials are much bigger and longer now……
Slide 7: Then…and now
Then…and now Rezulin (troglitazone) was approved in 1997 with less than 1,000 patients treated for 6 months When rivaroxaban was approved, over 60,000 patients had been exposed to the drug
Slide 8: Motif Bio Shares Plummet After Additional Iclaprim Clinical Trial Blow
Motif Bio Shares Plummet After Additional Iclaprim Clinical Trial Blow (ALLISS) LONDON (Alliance News) – Alliance News 6 June, 2019 | 10:07AM “On Thursday, Motif explained it had received the official minutes of its meeting with the FDA …(and) an additional clinical trial will be needed before grant
Slide 9: Economics of delay in FDA approval
Economics of delay in FDA approval If drug attains at least $1B/year in sales at the end of patent life Every day of delay in approval >$2 million 9
Slide 10: Drug-Induced Liver Injury (DILI)
Drug-Induced Liver Injury (DILI) 1). Remains a major problem in drug development, driving up drug costs and delaying release of new drugs. 2). Is also a rising problem with herbal and dietary supplements.
Slide 11: Don't forget Herbal and Dietary Supplements! DILIN Cohort
Don’t’ forget Herbal and Dietary Supplements! The Drug Induced Liver Injury Network (DILIN) Cohort September 2004 to May 2013 Top 10 therapeutic classes and individual agents to cause liver injury in the DILIN (N=899) Therapeutic Class n 1 Antimicrobials 408 2 Herbal and dietary 145 3 CVS agent 88 4
Slide 12: Before
Before In only 6 weeks of drinking FitTea™ Robert lost $500
Slide 13: Outline of Talk
Outline of Talk 1). Problem of liver safety 2). Current process to assess the safety of new drug candidates 3). Progress in QST modeling - DILIsym ® 4). Conclusions
Slide 14: Assessing Liver Safety of New Drug Candidates
Assessing Liver Safety of New Drug Candidates 1). Preclinical (non-clinical) studies a). Variety of molecular screening tools b). Animal models – rodent and non-rodent
Slide 15: Good drugs are being dropped at the preclinical stage
Good drugs are being dropped at the preclinical stage due to toxicity concerns…. Acetaminophen Ibuprofen 15
Slide 16: Assessing Liver Safety of New Drug Candidates
Assessing Liver Safety of New Drug Candidates 1). Preclinical (non-clinical) studies a). Variety of molecular screening tools b). Animal models – rodent and non-rodent 2). Clinical trials
Slide 17: Serum ALT is universally used to detect and monitor liver injury
Serum Alanine Aminotransferase (ALT) is universally used to detect and monitor liver injury • Protein present inside hepatocytes • Leaks into circulation during hepatocyte injury/death • Liver-specific if there is no muscle injury.
Slide 18: Problems with Serum ALT as a Biomarker for DILI in Clinical Trials
Problems with Serum ALT as a Biomarker for DILI in Clinical Trials 1). Some drugs cause ALT elevations yet are rarely associated with clinically important liver injury (e.g. statins, cholestyramine, heparins, tacrine) 2). ALT elevations generally resolve with continued treatment even for drugs that
Slide 19: General Approach to ALT elevations in Clinical Trials
General Approach to ALT elevations in Clinical Trials 1). Continue to treat through the elevations to see if global liver dysfunction occurs – i.e. a rise in serum bilirubin (“Hy’s Law Case”) 2). Large clinical trials may be needed to define risk
Slide 20: eDISH format for display of clinical trial liver safety data
eDISH format for display of clinical trial liver safety data 100.0 hyperbilirubinemia Hy's Law range Drug X Drug C Peak TBL, xULRR 10.0 2x ADAPTATION 1.0 normal range 3x Temple's Corollary range 0.1 0.1 1.0 10.0 100.0 Peak ALT, xULRR Ted Guo and John Senior 20
Slide 21: eDISH format for display of clinical trial liver safety data
eDISH format for display of clinical trial liver safety data 100.0 hyperbilirubinemia Hy's Law range Drug X Drug C Peak TBL, xULRR 10.0 2x 1.0 normal range 3x Temple's Corollary range 0.1 0.1 1.0 10.0 100.0 Peak ALT, xULRR Ted Guo and John Senior 21
Slide 22: Outline of Talk
Outline of Talk 1). Problem of liver safety 2). Current process to assess the safety of new drug candidates 3). Progress in QST modeling – DILIsym ® 4). Conclusions
Slide 23: UNC Institute for Drug Safety Sciences: The DILI-sim Initiative
UNC Institute for Drug Safety Sciences The DILI-sim Initiative Some Current Companies In the Initiative Patients In Vitro Cutting Edge Pre-clinical Models 23
Slide 24: DILI-sim Scientific Advisory Board
DILI-sim Scientific Advisory Board Dr. Neil Kaplowitz Dr. Paul B. Watkins Dr. Kevin Park Professor of Medicine DIRECTOR, INSTITUTE FOR DRUG SAFETY SCIENCES Head of Institute of Translational Medicine / USC Thomas H. Brem Chair in Medicine HOWARD Q. FERGUSON DISTINGUISHED Director, MRC Centre for Dru
Slide 25: DILI-sim Initiative Approach
DILI-sim Initiative Approach 1). Build mechanistic “modules” using differential equations – perform experiments to fill in knowledge gaps. 2). Integrate the modules with the outcome of hepatocyte death and release and clearance of traditional and novel serum biomarkers. 3). Vary model parameters to
Slide 26: DILIsym software created by the DILI-sim Initiative
DILIsym® software created by the DILI-sim Initiative Drug Metabolism and Distribution Unconjugated Reactive Metabolite Biliary Phospholipids Lipotoxicity Reactive Oxygen Species Biliary Mitochondria Dysfunction and Bile Acids Intracellular Bile Acids Toxicity Cholangiocyte Hepatocyte death/regenerat
Slide 27: DILIsym Input Data
DILIsym Input Data Exposure Pharmacokinetics Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury (ALT) ROS Generation SimPops™ Interpatient Variability Unique Parameter Combinations 27
Slide 28: DILIsym software created by the DILI-sim Initiative
DILIsym® software created by the DILI-sim Initiative Drug Metabolism and Distribution Unconjugated Reactive Metabolite Biliary Phospholipids Lipotoxicity Reactive Oxygen Species Biliary Mitochondria Dysfunction and Bile Acids Intracellular Bile Acids Toxicity Cholangiocyte Hepatocyte death/regenerat
Slide 29: AMG 009
AMG 009 No evidence of liver injury in multiple species • Rats, mice, hamsters, rabbits and non-human primates – During Phase I clinical trials in healthy volunteers, 5/8 patients showed significant and reversible transaminase elevations at the highest dose. – Development of AMG 009 was halted – BSE
Slide 30: Drugs Can Inhibit Bile Acid Transporters
Drugs Can Inhibit Bile Acid Transporters Hepatotoxicity MRP3/4 Bile Acids BSEP Drug - OA NTCP (OATP) Bile Acids Drug
Slide 31: DILIsym Input Data
DILIsym Input Data Exposure Pharmacokinetics Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury (ALT) ROS Generation SimPops™ Interpatient Variability Unique Parameter Combinations 31
Slide 32: DILIsym Predicts Dose-Dependent AMG 009 Hepatotoxicity in Human SimPops
DILIsym® Predicts Dose-Dependent AMG 009 Hepatotoxicity in Human SimPops™ Stop criteria HUMANS 100 mg BID 14 d Dose-Response used (25-100 mg BID 14 d) Treatment • DILIsym® predicts dose-dependent, delayed presentation of AMG 009 hepatotoxicity and recovery after discontinuation • Incidence rates wer
Slide 33: No Hepatotoxicity Predicted in the Rat SimPops Administered AMG 009
No Hepatotoxicity Predicted in the Rat SimPops™ Administered AMG 009 1500 mg/kg/day PO for 1 month 1500 mg/kg PO 1 month† Direct BA Toxicity Model No. Deaths 0/187 ALT > 3X 0/187 Bili > 2X 0/187 Treatment RATS Unpublished data Preclinical Data and 33 Simulation Results
Slide 34: AMG 853 more potent BSEP inhibitor than AMG 009
AMG 853 • AMG 853 was the backup to AMG 009 – No evidence of liver injury in preclinical species. – No evidence of human toxicity in clinical trials -- But..AMG 853 was a more potent BSEP inhibitor than AMG 009 with IC50’s of 4.3 vs. 11.5 µM respectively 34
Slide 35: DILIsym Modeling of AMG 853
DILSYM Modeling of AMG 853 • DILIsym predicted that AMG 853 was safe in simulated humans (SimPops™) • Exposure to AMG 853 is lower compared to AMG 009 at comparable doses; however, higher doses were simulated in DILIsym up to 50X the clinical dose and AMG 853 remained safe Why? - Inhibition type was
Slide 36: Why mechanism of transport inhibition matters
Why mechanism of transport inhibition matters Hepatotoxicity MRP3/4 Bile Acids BSEP 009 - OA NTCP (OATP) Bile Acids 009
Slide 37: Why mechanism of transport inhibition matters
Why mechanism of transport inhibition matters MRP3/4 Bile Acids BSEP 853 - OA NTCP (OATP) Bile Acids 853
Slide 38: Conclusion
Conclusion QST modeling was able to predict species differences in hepatoxic potential of AMG 009 and the safety of AMG 853 in man based on in vitro assessments of bile acid transporter inhibition …. Despite the fact that the BSEP IC50 (and Ki) were lower for 853 than 009
Slide 39: DILIsym predicted that single doses of CKA caused serum ALT>3 X ULN
“DILIsym predicted that single doses of CKA caused serum ALT>3 X ULN in a subset of the simulated rat population, while single doses in a simulated Human population did not produce serum ALT elevations. Species differences were largely attributed to differences in liver exposure, but increased sensi
Slide 40: Toxicological Sciences, 162(2), 499–508
TOXICOLOGICAL SCIENCES, 162(2), 499–508 2018
Slide 41: Comments from Will Proctor, Ph.D, Genentech
Comments from Will Proctor, Ph.D, Genentech Feb 25, 2018 We are targeting harder proteins such as GPCRs, ion channels, and previously "undruggable" targets by targeting them for degradation or affecting protein/protein interactions….. These (NMEs) are all typically BDDCS class 2 molecules, with high
Slide 42: Compound Y
Compound Y 1) Initially developed for one indication but Hy’s Law Cases were observed in the first in man clinical trial resulting in termination of the program. 2). Discovered to have a very potent interaction with another disease target. Question: Could lower dosing for this new disease indication
Slide 43: DILIsym Input Data
DILIsym Input Data Exposure Pharmacokinetics Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury (ALT) ROS Generation SimPops™ Interpatient Variability Unique Parameter Combinations 43
Slide 44: eDISH format for display of clinical trial liver safety data
eDISH format for display of clinical trial liver safety data 100.0 hyperbilirubinemia Hy's Law range Drug X Drug C Peak TBL, xULRR 10.0 2x 1.0 normal range 3x Temple's Corollary range 0.1 0.1 1.0 10.0 100.0 Peak ALT, xULRR Ted Guo and John Senior 44
Slide 45: Hepatotoxicity Predicted for Prior Clinical Protocols
Hepatotoxicity Predicted for Prior Clinical Protocols 0.3X Compound Y Dosing 0.5X Compound Y Dosing 1X Compound Y Dosing No clinical stop protocol 45 Simulation Results
Slide 46: No Hepatotoxicity Predicted for The Proposed Clinical Protocols
No Hepatotoxicity Predicted for The Proposed Clinical Protocols 0.07X/0.03X 0.13X/0.07 Compound Y Dosing Compound Y Dosing No clinical stop protocol Presented at face to face meeting with FDA division 46 Simulation Results
Slide 47: Conclusion
Conclusion At the lower dosing regimens proposed, compound Y may have an acceptable liver safety profile for the new disease indication.
Slide 48: Known DILIsym Applications Submitted to or Intended for Regulatory Agencies
Known DILIsym Applications Submitted to or Intended for Regulatory Agencies Presented/ N Agency Context Scenario Simulation Type Submitted By Simulation results included in formal, written Sponsor responding to concerns over liver safety Hepatocyte loss 1 FDA Sponsor correspondence to agency signals
Slide 49: DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity
DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity Exposure Pharmacokinetics Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury ROS Generation Analysis of Mechanisms SimPops™ Interpatient Variability Unique Paramete
Slide 50: DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity
DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity Exposure Pharmacokinetics Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury ROS Generation Analysis of Mechanisms SimPops™ Interpatient Variability Unique Paramete
Slide 51: DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity
DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity Exposure Pharmacokinetics Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury ROS Generation Analysis of Mechanisms SimPops™ Interpatient Variability Unique Paramete
Slide 52: DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity
DILIsym Integrates Multiple Inputs to Simulate/Predict Hepatotoxicity Exposure Understanding mechanisms can Pharmacokinetics identify patient risk factors Mechanisms Bile Acid Transporter Inhibition Simulated Frequency Mitochondrial & Severity of Liver Respiration Injury ROS Generation Analysis of M
Slide 53: Applications of DILIsym Along the Drug Development Pipeline
Applications of DILIsym Along the Drug Development Pipeline • Mechanism exploration • Dose optimization (risk versus presumed • Aid identification of risk • Rank candidates for DILI benefit) factors leading to potential • Infer magnitude of injury based on personalized medicine • Extrapolation from
Slide 54: Applications of DILIsym Along the Drug Development Pipeline
Applications of DILIsym Along the Drug Development Pipeline • Mechanism exploration • Dose optimization (risk versus presumed • Aid identification of risk • Rank candidates for DILI benefit) factors leading to potential • Infer magnitude of injury based on personalized medicine • Extrapolation from
Slide 55: Some Applications of DILIsym Along the Drug Development Pipeline
Some Applications of DILIsym Along the Drug Development Pipeline • Rank candidates for DILI • Dose optimization (risk versus presumed • Aid identification of risk potential benefit) factors leading to • Extrapolation from animal • Infer magnitude of injury based on personalized medicine and in vitro
Slide 56: How to access DILIsym
How to access DILIsym Academia: Low cost licenses available Industry: 1). Join DILI-sim Initiative 2). Licensing options For more information, google “DILIsym” or contact Brett Howell at bhowell@dilisym.com
Slide 57: New Renasym Consortium
New Renasym Consortium 1). $1.7 M Phase1/2 SBIR awarded. 2). Merck is first to join and will share data on species differences in kidney toxicity of NMEs including newer urine biomarker data.
Slide 58: RENAsym Scientific Advisory Board
Experts Who Have Agreed to Serve on the RENAsym Scientific Advisory Board Dr. Paul B. Watkins Dr. K. Melissa Hallow Dr. Zheng Dong Director, Institute for Drug Safety Sciences Assistant Professor Leon H. Charbonnier Endowed Chair, Regents Professor Howard Q. Ferguson Distinguished School of Chemical
Slide 59: RENAsym Version 1A Preview
RENAsym Version 1A Preview • Starting with well Ghezzi et al., Diabetologia 2018 • Species: human and rat known kidney toxicants - Population variability plus negative controls, such as cisplatin, • The three primary zones of gentamycin, and APAP the renal proximal tubule represented • Single and co
Slide 60: Outline of Talk
Outline of Talk 1). Problem of liver safety 2). Current process to assess the safety of new drug candidates 3). Progress in QST modeling – DILIsym ® 4). Conclusions
Slide 61: Conclusions
Conclusions • QST modeling is having a significant impact on decision making in drug development. • Its application should lead to reductions in improved safety of new drugs, smaller and smaller clinical trials, and reduction in animal testing.
Slide 62: How FDA Plans to Help Consumers Capitalize on Advances in Science
How FDA Plans to Help Consumers Capitalize on Advances in Science Posted on July 7, 2017 by FDA Voice By: Scott Gottlieb, M.D New FDA Commissioner “FDA’s Center for Drug Evaluation and Research (CDER) is currently using modeling and simulation to predict clinical outcomes, inform clinical trial desi
Slide 63: How FDA Plans to Help Consumers Capitalize on Advances in Science
How FDA Plans to Help Consumers Capitalize on Advances in Science Posted on July 7, 2017 by FDA Voice By: Scott Gottlieb, M.D New FDA Commissioner “FDA’s Center for Drug Evaluation and Research (CDER) is currently using modeling and simulation to predict clinical outcomes, inform clinical trial desi
Slide 64: The DILIsym Services Team
The DILIsym Services Team Paul B. Watkins DILI-sim Initiative Founder and Shawn O’Connor Scientific Advisory Board Chair Scott Q Siler Brett Howell CEO, Simulations Plus Inc. RTP, NC Chief Scientific Officer President Lancaster, CA Bay Area, CA RTP, NC Lisl Shoda Grant Generaux Jeff Woodhead Kyunghe