David Miller

David Miller

David Miller, Ph.D.
Vice President, Cheminformatics
Simulations Plus, Inc.

About David
David is Vice President of ADMET Cheminformatics in the Lancaster Division of Simulations Plus. He previously worked at Sage Informatics, a small cheminformatics software startup he founded in 2001 and that Simulations Plus acquired in 2005, as well as at Bioreason and CombiChem. He received his Ph.D. in Biophysics from the University of California at San Francisco. David is one of the lead software engineers for the ADMET Predictor software platform, where his primary responsibilities are the core chemistry engine and graphical user interface. He makes numerous presentations on ADMET Predictor at customer sites in the United States and abroad.

Latest Research by David Miller

03/20/2022

AI-driven Lead Discovery

Lawless M, Miller D, Waldman M

Keywords: admet predictor, AI-driven compound optimization, AIDD Module, BACE1 inhibitors, de novo designSoftware: ADMET Predictor®Conference: ACSDivision: Simulations Plus

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03/20/2022

Using artificial intelligence to design BACE1 inhibitors

Lawless M, Miller D, Clark RD, Waldman M

Keywords: admet predictor, AIDD Module, alzheimer's disease, BACE1 inhibitorsSoftware: ADMET Predictor®Conference: ACSDivision: Simulations Plus

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02/16/2022

Discovery Track: Pushing the Boundaries Beyond – NextGen Session Panel Discussion and Live Q&A

Miller D, Waldman M, Lawless M, Daga PR, Zin PP, Fraczkiewicz R

Keywords: Discovery Track, MIDD (model-informed drug development), MIDD+ 2022, modeling and simulation, SLP MIDD+ Virtual Conference, SLP2022MIDDConference: SLP MIDD+Division: Simulations Plus

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02/16/2022

Discovery Track: HTPK simulations using the new REST API + platform update

Miller D

Keywords: Discovery Track, HTPK, HTPK simulation module, MIDD (model-informed drug development), MIDD+ 2022, modeling and simulation, REST API, SLP MIDD+ Virtual Conference, SLP2022MIDDConference: SLP MIDD+

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02/10/2022

Predicting nonlinear relationships between external and internal concentrations with physiologically based pharmacokinetic modeling

Hoer D, Barton HA, Paini A, Bartels M, Ingle B, Domoradzki J, Fisher J, Embry M, Villanueva P, Miller D, Zhang Q, Edwards SW, Tan YM

Keywords: admet predictor, animal testing, chemicals, drug safety testing, gastroplus, Michaelis-Menten, nonlinear pk, PBPK modeling, risk assessment, toxicologyPublication: Toxicol Appl Pharmacol

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09/15/2021

ADMET Predictor® 10.3 (APX.3): Flagship machine learning platform for ADMET modeling

Miller D, Jamois E, Nevarez J

Keywords: admet predictor, AIDD, APX.3, cheminformaticsSoftware: ADMET Predictor®Division: Simulations Plus

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05/05/2021

ADMET Predictor® 10.2 (APX.2): Machine learning platform for ADMET modeling with extended capabilities for discovery PBPK

Jamois E, Miller B, Miller D

Keywords: admet predictor, APX.2, cheminformatics, HTPK simulation module, Simulations Plus, slpSoftware: ADMET Predictor®Division: Simulations Plus

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03/03/2021

Introduction to ADMET Predictor®

Miller D

Keywords: admet predictor, ADMET property prediction, cheminformatics, discovery, model building, PBPK simulation, SLP2021MIDDSoftware: ADMET Predictor®Conference: SLP MIDD+Division: Simulations Plus

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03/03/2021

Designing Novel Compounds with Optimized Target Activity and ADMET Properties Using the AIDD™ Module

Lawless M, Miller D, Waldman M

Keywords: ADMET prediction, AIDD, discovery, pharmacokinetics (PK), SLP2021MIDDSoftware: ADMET Predictor®Conference: SLP MIDD+Division: Simulations Plus

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09/30/2020

Delivering on the promise of AI-driven drug discovery with ADMET Predictor® 10 (APX). Background and applications examples

Lawless M, Miller D, Jamois E, Waldman M

Keywords: admet predictor, AI-driven compound optimization, AIDD, APXSoftware: ADMET Predictor®Division: Simulations Plus

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