Linear solvers · Biotech & Pharma
Conjugate Gradient (CG) for Biotech & Pharma
Apply the conjugate gradient (cg) to real biotech & pharma problems — in the browser, with AI assistance.
CG minimizes the residual over expanding Krylov subspaces, converging far faster than stationary methods for SPD systems common in FEM.
In biotech & pharma, teams face challenges like reaction kinetics, mixing and transport, regulatory validation. The conjugate gradient (cg) directly supports use cases such as enzyme kinetics, bioreactor mixing cfd, drug-diffusion modeling, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Biotech & Pharma use cases
- Enzyme kinetics
- Bioreactor mixing CFD
- Drug-diffusion modeling
Upgrade your workspace
Educator Classroom Kit — $45
Set up a class of 30 students for one term with shared projects.
Recommended products
Priority Support Pass
$1030 days of priority support responses.
Compute Usage Analytics Report
$3A breakdown of where your compute tokens are going.
Family / Group (5)
$29/moFive linked seats for a family or study group.
Sponsored Job Listing
$59/moPost a simulation-engineer role to our job board.
AI Copilot Credits ×50
$4Fifty extra AI Copilot generations for node-graph authoring.
Batch Render (100 frames)
$10Render a hundred frames of your simulation in one batch job.