Computational Biology: QSP, PBPK & Systems Pharmacology for Pharma
End-to-end computational biology services — QSP/PBPK modeling, bioinformatics pipelines, multi-omics data analysis, molecular modeling, and AI-driven solutions — purpose-built for pharmaceutical and biotech drug discovery.
What We Do
What Excelra Does in Computational Biology
Excelra is a scientific informatics company and leading computational biology services provider with 300+ experts helping pharmaceutical and biotech organizations make faster, data-driven drug discovery decisions. In computational biology, Excelra delivers QSP/PBPK modeling, quantitative systems pharmacology, molecular modeling and simulation, multi-omics data analysis, AI and machine learning solutions, and knowledge graph development — combining 15+ years of pharma expertise, cloud-native infrastructure, and proprietary databases to accelerate drug discovery from target identification through clinical development. Excelra’s computational biology services work in close conjunction with bioinformatics solutions and precision medicine analytics for end-to-end data science coverage. As a computational biology company specialising in pharma, Excelra’s work is grounded in FDA PBPK guidance and best practices in QSP modeling
Our Services
End-to-End Computational Biology Services
From QSP/PBPK modeling and systems pharmacology to multi-omics data analysis, molecular simulation, and AI-driven drug discovery — all connected to Excelra’s scientific informatics platform.
QSP / PBPK Modeling & Systems Pharmacology
Quantitative Systems Pharmacology (QSP) and PBPK modeling to predict drug behavior, optimize dose regimens, support go/no-go decisions, and accelerate IND submissions. Aligned with FDA PBPK guidance.
QSP/QST | PBPK | Systems Pharmacology
Omics Data Analysis & Biomarker Identification
Comprehensive omics data analysis — transcriptomics, proteomics, metabolomics — for biomarker identification and target discovery. Powered by GoBiom and FAIR data principles.
Transcriptomics | Proteomics| FAIR Data
Data Engineering & Pipeline Development
ETL pipelines for biological data processing, custom NGS and omics data pipelines, and cloud-native deployment on AWS, GCP, and Azure via OP 2.0.
ETL Pipelines | Cloud | NGS Data
AI-Driven Solutions & Machine Learning
Machine learning for genomic biomarker discovery, LLM-powered knowledge extraction, and explainable AI (XAI) for transparent drug candidate predictions. See our LLM oncology case study.
Machine Learning | LLMs | XAI
Molecular Modeling & Simulation
Virtual screening, scaffold hopping, and molecular dynamics simulation using GPU-powered tools to identify candidates and optimize compounds. Integrated with GoStar’s 14M+ compound SAR database and cheminformatics services.
Molecular Dynamics | Virtual Screening | GoStar
Knowledge Graphs & Ontology Management
Custom FAIR-aligned knowledge graphs connecting biomedical data, domain ontology development, and semantic data services for cross-platform integration and scientific data management.
Knowledge Graphs | Ontologies | FAIR
Interactive Dashboards & Visualizations
Data-driven decision support through custom dashboards using Power BI, Tableau, and R-Shiny, and the BioVisualizer™ platform for biological data visualization and miRNA analysis.
Power BI | Tableau | R-Shiny
In Silico Drug Discovery
Integrated in silico drug discovery combining DEL analysis, hit-to-lead optimization, target identification, and targeted protein degradation workflows via GoStar TPD.
In Silico | Target ID | DEL Analysis
Core Service · QSP Pharma Company
QSP / PBPK Modeling & Systems Pharmacology Services
Excelra’s Quantitative Systems Pharmacology (QSP) and PBPK modeling services provide mechanistic mathematical models that integrate drug pharmacology with patient physiology — helping pharma teams predict clinical outcomes, optimize dose regimens, support go/no-go decisions, and accelerate regulatory submissions. Our QSP/QST modeling is aligned with FDA PBPK guidance and EMA population PK guidelines.
✓ PBPK model development & validation
✓ Dose regimen optimization
✓ Regulatory submission support (FDA/EMA)
✓ Drug-drug interaction (DDI) prediction
✓ Pediatric & geriatric extrapolation
✓ Clinical pharmacology support
✓ Population PK/PD analysis
Talk to Excelra’s computational biology team today.
QSP/PBPK modeling · Systems pharmacology · Omics data analysis · AI/ML solutions
Computational Biology Services in Action
How pharma and biotech teams apply Excelra’s computational biology services across biopharma, diagnostics, and animal health. Browse all Excelra case studies.
How We Work
Frequently Asked Questions: Computational Biology Services
Common questions about QSP, PBPK, systems pharmacology, and Excelra’s computational biology services. For deep-dives visit our glossary, blogs, and whitepapers.
What computational biology services does Excelra offer?
Excelra offers end-to-end computational biology services including QSP/PBPK modeling, systems pharmacology, omics data analysis and biomarker identification, data engineering and pipeline development, molecular modeling and simulation, AI and machine learning solutions, knowledge graph development, and FAIR data management — delivered by 300+ scientific informatics experts.
What is QSP modeling and how does Excelra use it in drug discovery?
Quantitative Systems Pharmacology (QSP) integrates drug pharmacology with biological systems to predict drug behavior and efficacy across patient populations. Excelra’s QSP/QST modeling services help pharma teams optimize dose regimens, predict clinical outcomes, and support IND submissions. Excelra’s iQSP platform supports end-to-end QSP workflows aligned with FDA PBPK guidance.
What is PBPK modeling and does Excelra provide PBPK services?
Physiologically Based Pharmacokinetic (PBPK) modeling uses anatomical, physiological, and biochemical parameters to predict drug ADME (absorption, distribution, metabolism, excretion) in the body. Excelra provides PBPK modeling services for dose optimization, DDI prediction, pediatric/geriatric extrapolation, and regulatory submissions. Learn more at the QSP glossary.
What is the difference between computational biology and bioinformatics?
Computational biology applies mathematical modeling and simulation to understand biological system behavior — including QSP/PBPK modeling, molecular dynamics, and systems pharmacology. Bioinformatics focuses on algorithms and pipelines for processing biological datasets (genomics, transcriptomics, proteomics). Excelra provides both — computational biology for systems modeling, and bioinformatics for data analysis pipelines and disease landscape analysis.
What omics data analysis services does Excelra offer?
Excelra’s omics data analysis services cover transcriptomics, proteomics, metabolomics, and multi-omics integration for biomarker identification, target discovery, and precision medicine. Services include FAIR data management, ETL pipeline development, and interactive dashboards using Power BI, Tableau, and R-Shiny.
How does Excelra use AI and machine learning in computational biology?
Excelra applies AI and machine learning across computational biology workflows — genomic biomarker discovery using supervised learning, knowledge graph construction using LLMs, and explainable AI (XAI) for transparent predictions. Molecular modeling leverages GPU-powered tools for virtual screening, scaffold hopping, and molecular dynamics simulation. See: LLM oncology data platform case study.
Does Excelra offer computational biology services for biotech startups?
Yes. Excelra works with biotech startups through flexible engagement models — providing QSP/PBPK modeling, omics data analysis, and AI-driven drug discovery capabilities without the overhead of an in-house team. Cloud-native infrastructure (AWS, GCP, Azure) ensures scalable, cost-efficient delivery.
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