Solutions > ML/AI-Driven Target Discovery and Computational Systems Biology

ML/AI-driven Target Discovery and Computational Systems Biology

Analyzing and extracting insights from scientific data is a complex challenge. Structured and unstructured data from diverse sources, including vast amounts of molecular and imaging data, add to the difficulty of mining for information on disease mechanisms and potential targets. bPrescient can help, with sophisticated, multi-omic ML- and AI-based methods for target identification and validation, and for complex disease understanding.

Solution Overview Solution Benefits Relevant Expertise Example Tools and Data Sources

Solution Overview

Our solution for ML/AI-driven target discovery and systems biology includes:

Data strategy for managing and organizing public and internal data using data lakes, database warehouses, or federated models.
Processes for structuring analytics to enable reproducibility and provenance of results, using tools like DNAnexus, DataBricks, and Quilt Data.
Fit-for-purpose analytics development using machine learning and AI for analyzing multi-omics data for biological insights and disease-relevant signals.
Implementation of laboratory data systems such as LIMS and ELNs to provide well-annotated data that is connected to relevant subject and sample information.
Design and implementation of data analysis pipelines for robust and efficient processing of large-scale molecular and imaging data sets.

Solution Benefits

Partnering with bPrescient benefits your R&D program in a variety of ways:

Gain a holistic understanding of molecular evidence for targets and pathways in disease and normal biology.
Quickly form disease target hypotheses coupled with data and literature support, along with evidence for potential biomarkers.
Achieve efficient processing of large-scale data sets and support reuse for multiple therapeutic programs and modalities.
Enable tracking of results back to samples and clinical subjects through robust data and metadata management.

Relevant Expertise

This service draws on our expertise in the following areas:

Strategy & Roadmap Development
Scientific Informatics: Software Design and Implementation
Laboratory Data Systems Design, Integration & Optimization
AI & Machine Learning: Generating Novel Insights
Computational Sciences for Biology & Chemistry Research
Data Engineering, MLops, and CloudOps

Learn more about our expertise

Example Tools and Data Sources

We use a variety of tools and data sources to meet specific client needs, including the following:

Data Sources

PubMed
Genbank
The Cancer Genome Atlas
KeGG
DepMap
UK Biobank
Thomson Reuters
Qiagen IPA

Tools

Bioconductor / R
Python / Biopython
DataBricks
Snowflake
Quilt Data
DNAnexus
AlphaFold
SimTK
RoseTTAFold
RFdiffusion
Boltz-1

Related Case Studies

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Let’s talk

Tell us about your toughest R&D challenge and let’s discuss how bPrescient can solve it.

ML/AI-driven Target Discovery and Computational Systems Biology

Solution Overview

Solution Benefits

Relevant Expertise

Example Tools and Data Sources

Related Case Studies

Target Discovery Portal Development

Target Discovery Platform Design & Implementation

Multi-Modal Machine Learning For Target Discovery

ML Driven Target and Biomarker Data Mining

Let’s talk