Company · founded 1983
Simulation Technologies (United States)
Huntsville, United States · simtechinc.com
- Citations, last 5 years
- 144
- Works, last 5 years
- 54
- h-index
- 22
- Scientists listed
- 3
- Grants since 2016
- 8
Grants received
2024 · research · R43
Binding free energy predictions for peptide drugs: A novel machine learning-based peptide simulation model for high-throughput computational lead optimization with quantum mechanical accuracy.
Alec White · Simulation Technologies (United States) · funded by National Institutes of Health
2023 · research · R43
Next generation free energy perturbation (FEP) calculations--enabled by a novel integration of quantum mechanics (QM) with molecular dynamics allowing a large QM region and no sampling compromises
David A Pearlman · Simulation Technologies (United States) · funded by National Institutes of Health
2023–2024 · research · R43
Absolute binding free energies for virtual screening: A novel implementation of quantum mechanics/molecular mechanics (QM/MM) for FEP that allows substantial sampling and a significant quantum region
David A Pearlman · Simulation Technologies (United States) · funded by National Institutes of Health
2021–2022 · grant · Standard Grant
SBIR Phase I: Creation of a virtual population of older, black patients with hypertension and comorbidities for improved treatment development
William Pruett · Simulation Technologies (United States) · funded by National Science Foundation
2018 · grant · Standard Grant
SBIR Phase I: Helping Students Acquire 21st Century Skills Through Immersive Group STEM Simulations
Anthony Carr · Simulation Technologies (United States) · funded by National Science Foundation
2016–2017 · research · R43
A Computer Model of Renal Physiology for use as a FDA Medical Device Development Tool
William Andrew Pruett · Simulation Technologies (United States) · funded by U.S. Food and Drug Administration
2016–2017 · grant · Standard Grant
SBIR Phase I: Advancing Simulations with Clinical Scenarios to Enhance Biomedical Training
Richard Tallman · Simulation Technologies (United States) · funded by National Science Foundation
2016–2020 · research · R44
A Computer Model of Renal Physiology for use as a FDA Medical Device Development Tool
William Andrew Pruett · Simulation Technologies (United States) · funded by U.S. Food and Drug Administration