InsightRX Astra AI-Powered Clinical Trial Analysis

PK/PD analysis is bottlenecked by tooling, not by science

Scientific teams in regulated drug development face the same structural gap regardless of therapeutic area or study type: the distance between what they know and what they can execute.

Domain experts with deep PK/PD knowledge can't act on it directly without strong programming skills. Data preparation, NCA, population modeling, simulation, and TLF generation live in disconnected tools, forcing manual handoffs at every boundary. Meeting 21 CFR Part 11 and GxP standards manually turns every analysis into a separate documentation exercise, introducing risk at each stage. The result: scripting, debugging, and reformatting consume the calendar while scientific interpretation gets squeezed.

From bottleneck to breakthrough

Astra removes the barriers that slow pharmacometric teams, from disconnected tools and manual coding to compliance overhead, so scientists can focus on science.

Iterate at the speed of thought

Astra shifts analysis from writing code to asking questions, delivering standardized, reproducible, ready-to-run workflows in minutes, not days.

The power of analysis, directly in your hands

Astra empowers scientists to run sophisticated analyses independently, without dependency on specialists or programming expertise.

One platform, from data to deliverable

Astra unifies data preparation, analysis, and reporting in one platform, eliminating tool switching, manual handoffs, and format mismatches.

Compliance and auditability built in, not bolted on

Glass box architecture, built on validated R packages, ensures every output is fully-explainable and reproducible. Every action is logged, customer data never leaves your environment, and 21 CFR Part 11 and GxP compliance is built in by design.

In a design partner study, Astra was evaluated against standard clinical pharmacology workflows across multiple study types.

Results were consistent across all participants regardless of experience level.

4x more efficient on average vs. standard clinical pharmacology workflows

Open by design

Run the engines
you trust.

Astra runs the modeling engines your science already relies on. You keep the methods you trust, with no lock-in to a single vendor and no black box. Choose the NCA library and modeling engine that fit your environment, and let Astra handle the orchestration, code generation, reproducibility, and audit trail around whatever you pick.

The same openness runs through the platform: multiple NCA libraries and industry-standard simulation solvers, all inside one compliant, auditable environment.

Astra supports leading modeling engines, including:

NONMEM

The industry standard for population PK/PD modeling.

nlmixr2

FDA-accepted, open-source nonlinear mixed-effects modeling.

FeRx

InsightRX's open-source Rust engine, built for speed and ML-native modeling.

More on the way...

New engines added as your science demands them. Bring the tools your team already runs.

Astra's approach in the literature

Two articles in Clinical and Translational Science, co-authored by InsightRX, map where AI is heading in clinical pharmacology and reference Astra as an example of the approach in practice.

Agents for Change: Artificial Intelligent Workflows for Quantitative Clinical Pharmacology and Translational Sciences

Shahin MH, Goswami S, Lobentanzer S, Corrigan BW

Why general-purpose LLMs fall short in clinical pharmacology, and why orchestrated, domain-specific agents with human oversight are the answer. The approach Astra takes.

View publication →

Large Language Models and Their Applications in Drug Discovery and Development: A Primer

Lu J, Choi K, Eremeev M, Gobburu J, Goswami S, Liu Q, Mo G, Musante CJ, Shahin MH

Where LLMs genuinely accelerate drug development, and where reproducibility, provenance, and privacy have to be engineered in. Astra answers each by design.

View publication →

Validated against standard tools in a real-world study

In a design partner study, Astra was evaluated against standard clinical pharmacology workflows. Results were consistent across all participants and study types.

31%

More accurate than standard tools

97% vs. 74% with standard workflows, validated across SAD, MAD, and rBA study types.

4x

More efficient on average

19.8 points attempted per hour vs. 3.7 with standard tools; a 435% improvement over baseline

3.4x – 8.1x

Per-person efficiency gains

Consistent improvement across all experience levels, validated across SAD, MAD, and rBA study types.

InsightRX design partner study · Data on file.