Computational Biology. From Target to Trial.
Target identification, biomarker discovery, pharmacogenomics, large-cohort genomics, multi-omics integration, and regulatory bioinformatics — the intelligence layer pharma R&D teams need but can't scale in-house. PhD-led. NDA-first. India pricing.
Your CRO Runs the Trial.
Who Runs the Computational Biology?
Large CROs handle trial operations — randomization, site management, data collection, regulatory filing. But the computational biology that powers modern drug development sits in a different skill set entirely: genomic target validation, biomarker-driven patient stratification, pharmacogenomic dose optimization, multi-omics mechanism-of-action studies. Your internal comp bio team is overloaded. Your CRO doesn't offer it. That's the gap Genix fills.
Before the Trial
Target identification from multi-omics. Biomarker panel design. Companion diagnostics gene selection. Patient stratification models. Computational validation before wet-lab investment.
During the Trial
Pharmacogenomic response stratification. Genomic data from trial patients analysed in real-time. Responder vs non-responder molecular signatures. Dose-genotype correlation.
After the Trial
Real-world evidence from genomic cohorts. Multi-omics outcome correlation. PRS validation in diverse populations. Regulatory bioinformatics documentation for submission packages.
Full-Stack Translational Bioinformatics
Each capability available standalone or as part of integrated multi-phase engagements. Every deliverable PhD-reviewed, NDA-protected, and regulatory-ready.
Target Identification & Validation
Computationally identify and validate drug targets from multi-omics data before committing to wet-lab validation. Integrates GWAS hits, transcriptomic dysregulation, protein interactome networks, and druggability assessment to prioritize targets with the highest probability of clinical success.
Biomarker Discovery & Companion Diagnostics
Machine learning–driven biomarker discovery from genomic, transcriptomic, and proteomic data. Design companion diagnostic gene panels, build patient stratification models, and validate signatures across independent cohorts. Deliverables formatted for regulatory CDx submissions.
Pharmacogenomics (PGx) Analytics
Variant-drug interaction analysis, metaboliser phenotype prediction (CYP2D6, CYP2C19, CYP3A4, DPYD, UGT1A1, TPMT), and population-specific pharmacogenomics using South Asian allele frequencies from gnomAD SAS — a Genix differentiator for Indian-population clinical trials. Dose optimisation modelling and actionable PGx reporting.
Large Cohort Genomic Analysis
Analyse 1,000 to 100,000+ samples — GWAS, PRS development and validation, rare variant burden testing, structural variant detection, and ancestry-adjusted analysis. Pipelines compatible with UK Biobank, All of Us, and GenomeIndia data formats. Cloud-native (AWS Batch / Nextflow) for unlimited horizontal scaling.
Multi-Omics Data Integration
Joint analysis of RNA-Seq + ATAC-Seq + proteomics + metabolomics for mechanism-of-action studies. Use MOFA+, DIABLO, weighted gene co-expression networks, and network-based integration to find convergent biology that single-omic analysis misses. Published in Nature-tier frameworks.
Regulatory Bioinformatics Support
Documentation and validation support for NGS-based diagnostic submissions. Analytical validation reports (sensitivity, specificity, reproducibility, limit of detection), bioinformatics pipeline validation documentation, and methods sections for FDA 510(k)/PMA, CE-IVD, and CDSCO SaMD submissions.
Flexible Engagement Structures
Project-based, milestone-based, or annual retainer — structured to match how pharma procurement works.
| Capability | Starting At | Typical Range | Timeline | Billing |
|---|---|---|---|---|
| Target Identification & Validation | $20,000 | $20K–$75K | 4–8 weeks | Milestone (40/30/30) |
| Biomarker Discovery & CDx Design | $25,000 | $25K–$100K | 6–12 weeks | Milestone (30/30/20/20) |
| Pharmacogenomics Analytics | $15,000 | $15K–$60K | 3–6 weeks | 50/50 |
| Large Cohort Analysis (1K–100K samples) | $30,000 | $30K–$200K | 4–12 weeks | Milestone + cloud compute pass-through |
| Multi-Omics Integration | $25,000 | $25K–$100K | 6–12 weeks | Milestone (40/30/30) |
| Regulatory Bioinformatics | $15,000 | $15K–$50K | 4–8 weeks | 50/50 |
| Annual Retainer (Pharma Enterprise) | $8,000/mo | $8K–$20K/mo | 12-month term | Monthly advance, Net-15 |
NDA-First Workflow
Mutual NDA executed before any data exchange, scoping discussion, or methodology sharing. Pre-signed NDA available — sent within 1 hour of request.
Cloud Compute Transparency
Large cohort projects include cloud compute as a pass-through cost (AWS at-cost + 15% management). No hidden markup. Compute estimated upfront and capped in the proposal.
vs Western CRO Pricing
50–60% below Fios Genomics, Rancho Biosciences, Eurofins equivalents. Same pipelines (GATK, REGENIE, MOFA+), same PhD quality, India cost structure.
Why Pharma R&D Teams Choose Genix
PhD Founder Leads Every Engagement
Not a project manager routing work to juniors. The PhD founder personally scopes, reviews, and signs off on every pharma deliverable. Your programme director talks to our PhD, not a sales rep.
South Asian Population Genomics Expertise
gnomAD SAS allele frequencies integrated into every analysis. Critical for Indian-population clinical trials, where Western reference panels miss population-specific variants. A genuine differentiator no Western CRO offers.
Full Stack — Pre-Clinical Through Regulatory
Target ID → docking → biomarkers → PGx → cohort analysis → regulatory documentation. One partner across the entire computational biology lifecycle. No multi-vendor coordination overhead.
Days, Not Quarters
Internal teams have 4–8 week queues. Western CROs take 2–4 weeks to onboard. Genix delivers first milestone in 1–2 weeks. Your programme timeline doesn't wait for vendor bureaucracy.
Enterprise-Grade Data Security
NDA before data exchange. SFTP with key-based auth. LUKS-encrypted storage. AWS ap-south-1 data residency. 90-day post-project deletion. SOC 2 Type 1 on roadmap. Your compounds and patient data are safe.
Platform Upgrade Path
Start with project-based services. Graduate to the Genix Bioinformatics SaaS Platform for self-serve analysis at scale ($18K–$300K/yr). Services → SaaS = one seamless partner, growing with your needs.
Flexible Engagement Structures
Project-based, milestone-based, or annual retainer — structured to match how pharma procurement works.
| Capability | Starting At | Typical Range | Timeline | Billing |
|---|---|---|---|---|
| Target Identification & Validation | $20,000 | $20K–$75K | 4–8 weeks | Milestone (40/30/30) |
| Biomarker Discovery & CDx Design | $25,000 | $25K–$100K | 6–12 weeks | Milestone (30/30/20/20) |
| Pharmacogenomics Analytics | $15,000 | $15K–$60K | 3–6 weeks | 50/50 |
| Large Cohort Analysis (1K–100K samples) | $30,000 | $30K–$200K | 4–12 weeks | Milestone + cloud compute pass-through |
| Multi-Omics Integration | $25,000 | $25K–$100K | 6–12 weeks | Milestone (40/30/30) |
| Regulatory Bioinformatics | $15,000 | $15K–$50K | 4–8 weeks | 50/50 |
| Annual Retainer (Pharma Enterprise) | $8,000/mo | $8K–$20K/mo | 12-month term | Monthly advance, Net-15 |
NDA-First Workflow
Mutual NDA executed before any data exchange, scoping discussion, or methodology sharing. Pre-signed NDA available — sent within 1 hour of request.
Cloud Compute Transparency
Large cohort projects include cloud compute as a pass-through cost (AWS at-cost + 15% management). No hidden markup. Compute estimated upfront and capped in the proposal.
vs Western CRO Pricing
50–60% below Fios Genomics, Rancho Biosciences, Eurofins equivalents. Same pipelines (GATK, REGENIE, MOFA+), same PhD quality, India cost structure.
Why Pharma R&D Teams Choose Genix
PhD Founder Leads Every Engagement
Not a project manager routing work to juniors. The PhD founder personally scopes, reviews, and signs off on every pharma deliverable. Your programme director talks to our PhD, not a sales rep.
South Asian Population Genomics Expertise
gnomAD SAS allele frequencies integrated into every analysis. Critical for Indian-population clinical trials, where Western reference panels miss population-specific variants. A genuine differentiator no Western CRO offers.
Full Stack — Pre-Clinical Through Regulatory
Target ID → docking → biomarkers → PGx → cohort analysis → regulatory documentation. One partner across the entire computational biology lifecycle. No multi-vendor coordination overhead.
Days, Not Quarters
Internal teams have 4–8 week queues. Western CROs take 2–4 weeks to onboard. Genix delivers first milestone in 1–2 weeks. Your programme timeline doesn't wait for vendor bureaucracy.
Enterprise-Grade Data Security
NDA before data exchange. SFTP with key-based auth. LUKS-encrypted storage. AWS ap-south-1 data residency. 90-day post-project deletion. SOC 2 Type 1 on roadmap. Your compounds and patient data are safe.
Platform Upgrade Path
Start with project-based services. Graduate to the Genix Bioinformatics SaaS Platform for self-serve analysis at scale ($18K–$300K/yr). Services → SaaS = one seamless partner, growing with your needs.
Pharma Questions
Can you handle 50,000+ sample GWAS cohorts?
What makes your PGx analysis different for Indian populations?
Can your biomarker results be used in regulatory CDx submissions?
How do you handle IP and confidentiality for proprietary drug programmes?
What if we need a quick pilot before a full engagement?
Do you support multi-year pharma partnerships?
Describe Your
Programme. We'll Design
the Computational Strategy.
NDA-first. Scoping call within 48 hours. Methodology note and proposal within 1 week. No obligation.
Response Time
NDA within 1 hour. Scoping call within 48 hours.
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Genix.ai is an AI-powered clinical platform using NGS and imaging to detect biomarkers early, enabling clinicians to deliver cost-effective, personalized treatments for rare pediatric conditions, cancer care, and infectious diseases.
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