Simulations Plus, Inc. · NASDAQ:SLP
Simulations Plus — World Preclinical Congress Europe 2018
34 slides from Simulations Plus's conference presentation, Nov 27, 2018
Slide 1: Use of a QSP Model to Predict Liver Toxicity in Simulated Populations
Use of a Quantitative Systems Pharmacology (QSP) Model to Predict Liver Toxicity in Simulated Populations November 27, 2018 World Preclinical Congress Europe Christina Battista, Ph.D. Postdoctoral Fellow, Institute for Drug Safety Sciences, UNC Eshelman School of Pharmacy Institute for Drug Safety S
Slide 2: Disclaimer
Disclaimer • I am externally funded by DILIsym Services, Inc., a company that licenses the DILIsym software for commercial use and serves as the coordinating member of the DILI-sim Initiative. • I have a financial stake in DILIsym Services, Inc. Institute for Drug Safety Sciences CONFIDENTIAL 2
Slide 3: DILIsym Summary
DILIsym Summary • DILIsym is a mechanistic, mathematical model that has been constructed to support pharmaceutical risk assessment and decision making • Intersection of compound distribution and metabolism (PBPK), hepatotoxicity mechanisms, and patient variability • Core focus on explaining and pred
Slide 4: DILIsym Services, Inc.
DILIsym Services, Inc. “Our vision is safer, effective, more affordable medicines for patients through modeling and simulation.” • DILIsym Services, Inc. offers comprehensive program services: • DILIsym software licensing, training, development (DILI-sim Initiative) • NAFLDsym software licensing, tr
Slide 5: Your "End-to-End" Software Provider
Simulations Plus Inc. (NASDAQ: SLP): Your “End-to-End” Software Provider HO Discovery Preclinical Clinical CH3 N H O CH3 H3C O ADMET Predictor™ GastroPlus™ MedChem Studio™ DDDPlus™ PKPlus™ KIWI™ MedChem Designer™ MembranePlus™ DILIsym® NAFLDsym® Consulting Services and Collaborations Institute for D
Slide 6: Outline
Outline • Overview of the DILI-sim Initiative • Overview of the DILIsym Software • Application Example: In vitro to in vivo extrapolation • Summary Institute for Drug Safety Sciences CONFIDENTIAL 6
Slide 7: The DILI-sim Initiative is a Partnership between DILIsym Services and Pharmaceutical Companies
The DILI-sim Initiative is a Partnership between DILIsym Services and Pharmaceutical Companies to Minimize DILI • Overall Goals • Improve patient safety through quantitative systems toxicology (QST) • Reduce the need for animal testing • Reduce the costs and time necessary to develop new drugs • His
Slide 8: The Evolution of the DILI-sim Initiative
The Evolution of the DILI-sim Initiative 2012 Stage 1 2015 Stage 2 2018 Stage 3 Mechanisms Mechanisms Mechanisms • Reactive metabolites • Lipotoxicity • Adaptive immunity SLP • Oxidative stress • Innate immunity • Cholestasis Software Advances • Mitochondrial toxicity • Improve in vitro assay • Bile
Slide 9: Support of the DILI-sim Initiative Has Led to Significant Research Achievements
Support of the DILI-sim Initiative Has Led to Significant Research Achievements • Seven versions of DILIsym released, including DILIsym v7A in Jan 2018 • At least 18 applications of DILIsym directly related to regulatory submissions for drug development (that we are aware of) • More than 35 pharmace
Slide 10: Outline
Outline • Overview of the DILI-sim Initiative • Overview of the DILIsym Software • Application Example: In vitro to in vivo extrapolation • Summary Institute for Drug Safety Sciences CONFIDENTIAL 10
Slide 11: Applications of DILIsym Along the Drug Development Pipeline
Applications of DILIsym Along the Drug Development Pipeline Predictions of hepatotoxicity for humans and preclinical animal models • Mechanism exploration • Dose optimization (risk versus presumed benefit) • Inform choice and timing of biomarker • Rank candidates for DILI potential • Infer magnitude
Slide 12: DILIsym Predicts DILI via the Intersection Between Exposure, Mechanisms, and Liver Biochemistry
DILIsym Predicts DILI via the Intersection Between Exposure, Mechanisms, and Liver Biochemistry DILI Mechanisms Exposure DILI Relevant Liver Biochemistry Institute for Drug Safety Sciences CONFIDENTIAL 12
Slide 13: DILIsym: Quantitative Systems Toxicology
DILIsym: Quantitative Systems Toxicology Mitochondrial dysfunction Cellular life-cycle Drug distribution & metabolism Patient variability (SimPops) Kuepfer 2010, Molecular Systems Biology Institute for Drug Safety Sciences CONFIDENTIAL 13
Slide 14: DILIsym Overview
DILIsym Overview • Multiple species: human, rat, mouse, and dog - Population variability • The three primary acinar zones of liver represented • Essential cellular processes represented to multiple scales in interacting sub-models • Pharmacokinetics • Dosing (IP, IV, Oral) • Transporter Inhibition •
Slide 15: DILIsym Utilizes Various Data Types to Inform Decisions
DILIsym Utilizes Various Data Types to Inform Decisions Modeling & Exposure Data Simulation PBPK Modeling • Compound Properties Simulations and Assays inform: - Tissue partition coefficients • Prediction of DILI risk • Tissue penetration studies • Participating DILI mechanisms - Liver to blood ratio
Slide 16: Range of Hepatotoxic Responses in SimPops Due to Variability in Underlying Biochemistry
Range of Hepatotoxic Responses in SimPops Due to Variability in Underlying Biochemistry • SimPops are population samples with variability in hepatotoxic drug responses • Multiple parameters are varied to produce diverse simulated patients Variables Used to Construct SimPops • Numerous simulated pati
Slide 17: Outline
Outline • Overview of the DILI-sim Initiative • Overview of the DILIsym Software • Application Example: In vitro to in vivo extrapolation • Summary Institute for Drug Safety Sciences CONFIDENTIAL 17
Slide 18: Example Project Goal – Assess Compound X and Compound Y
Example Project Goal – Assess Compound X and Compound Y • The primary goal of this simulation work within the DILIsym software was to: • quantitatively and mechanistically assess the liver toxicity potential of Compound X and Compound Y combining clinical and mechanistic in vitro data with DILIsym a
Slide 19: Saying "I do" to the QSAR / PBPK / QST marriage…
Saying “I do” to the QSAR / PBPK / QST marriage… Permeability, Local & systemic solubility vs. pH, exposure, drug pKa(s), distribution, logD vs. pH, parent and Fup, metabolite levels, blood:plasma patient variability ratio, tissue Kps, CLint, CLfilt Institute for Drug Safety Sciences CONFIDENTIAL 19
Slide 20: GastroPlus PBPK Model Used to Predict Liver Exposure of Compound Y and Compound X
GastroPlus PBPK Model Used to Predict Liver Exposure of Compound Y and Compound X • Data on Compound Y and Compound X pharmacokinetics not available in the literature • No plasma time courses available; no in vitro or animal studies available either • In vitro data on liver distribution available fr
Slide 21: Compound Y PBPK Representation Calculated at Clinical Dose
Compound Y PBPK Representation Calculated at Clinical Dose Compound Y • GastroPlus predictions for liver and plasma at clinical dose shown at right • PBPK model specific predictions shown below • Dose escalation was simulated Simulation Results Institute for Drug Safety Sciences CONFIDENTIAL 21
Slide 22: Compound X PBPK Representation Calculated at Predicted Clinical Dose
Compound X PBPK Representation Calculated at Predicted Clinical Dose Compound X • GastroPlus predictions for liver and plasma at clinical dose shown at right • PBPK model specific predictions shown below • Dose escalation and alternate protocols were also simulated Simulation Results Institute for D
Slide 23: Mitochondrial Toxicity Parameters Determined for Compound Y and Compound X
Mitochondrial Toxicity Parameters Determined for Compound Y and Compound X • Parameter values were fit to mitochondrial data for Compound Y and Compound Y Compound X • Electron transport chain inhibition for Compound Y • Both electron transport chain inhibition and uncoupling for Compound X • 24 hou
Slide 24: Oxidative Stress Parameters Determined for Compound Y and Compound X
Oxidative Stress Parameters Determined for Compound Y and Compound X • Parameter values were fit to 24-hour ROS data for Compound Y Compound Y and Compound X • DILIsym representation of in vitro environment used to parameterize both compounds Compound X Compound Y Compound X DILIsym Parameter Units
Slide 25: Compound Y Weakly Inhibits BSEP; Compound X Does Not
Compound Y Weakly Inhibits BSEP; Compound X Does Not • Compound Y is a low-potency inhibitor of BSEP Compound Y; Ki = 140 mM, a = 0.6 • Compound Y also inhibits MRP4 transport (not shown) • Compound X does not inhibit BSEP • No changes to Vmax or Km of transporters observed over course of assay • Co
Slide 26: DILIsym Toxicity Parameters for Compound Y and X
DILIsym Toxicity Parameters for Compound Y and X DILIsym Parameter Value* Mechanism Parameter Unit Compound Y Compound X Coefficient for ETC µM 38,000 Not used inhibition 1 Coefficient for ETC µM 0.1 4,200 Inhibition 3 Max inhibitory effect dimensionless 0.2 0.4 Mitochondrial for ETC inhibition 3 Dy
Slide 27: SimPops Results Show Compound X and Compound Y to be Safe at Clinical Doses
SimPops Results Show Compound X and Compound Y to be Safe at Clinical Doses; ALT Elevations Predicted to Occur at Higher Doses for Both Compounds Simulated* • Neither Compound Y nor Compound X are Compound Dosing Protocol ALT > 3X ULN** predicted to cause toxicity at the highest clinical dose 1X Dos
Slide 28: SimPops Results Show Lack of Severe Liver Injury for Both Compounds at Clinical Doses
SimPops Results Show Lack of Severe Liver Injury for Both Compound Y and Compound X at Clinical Doses Compound Y; 1X Dose, 12 weeks Compound Y; 2X Dose, 12 weeks Compound Y; 5X Dose, 12 weeks Compound Y; 10X Dose, 12 weeks Hyperbilirubinemia Hy’s Law Range Hyperbilirubinemia Hy’s Law Range Hyperbili
Slide 29: Comparison with Competitors Suggests Compound X Has a Differentiated Liver Safety Profile
Comparison with Competitors Suggests Compound X Has a Differentiated Liver Safety Profile 1X Dose, 1X Dose, 1X Dose, 1X Dose Regimen 1 Regimen 2 Regimen 3 0.5X Dose 1X Dose Competitor A Competitor B Compound X Simulation Results Institute for Drug Safety Sciences CONFIDENTIAL 29
Slide 30: Comparison with Compound Y Competitor Suggests Comparable Liver Safety Profile
Comparison with Compound Y Competitor Suggests Comparable Liver Safety Profile 1X Dose 1X Dose Clinical trial results recently confirmed Compound Y Predictions Competitor C Compound Y Simulation Results Institute for Drug Safety Sciences CONFIDENTIAL 30
Slide 31: Example Project Summary
Example Project Summary • ADMET Predictor™ and GastroPlus™ software, along with in vitro data, was used to construct PBPK representations to predict liver exposures for both compounds • DILIsym parameters were successfully calculated from in vitro data for both compounds • SimPops results show Compo
Slide 32: Outline
Outline • Overview of the DILI-sim Initiative • Overview of the DILIsym Software • Application Example: In vitro to in vivo extrapolation • Summary Institute for Drug Safety Sciences CONFIDENTIAL 32
Slide 33: Summary
Summary • A combination of multiple mechanistic, in silico modeling approaches can facilitate drug discovery (QSAR, PBPK, QSP and QST) • DILIsym is a mechanistic, mathematical model that has been constructed to support pharmaceutical risk assessment and decision making • DILIsym simulation results h
Slide 34: Acknowledgements
Acknowledgements Paul B. Watkins DILI-sim Initiative Scott Q Siler Brett Howell Shawn O’Connor Scientific Advisory Board Chair CEO, Simulations Plus Inc. Chief Scientific Officer President RTP, NC Lancaster, CA Bay Area, CA RTP, NC Lisl Shoda Grant Generaux Jeff Woodhead Kyunghee Yang Principal Scie
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