AI Drug Discovery
A bench-ready hit list, at a fraction of physical screening cost
USD 35–95K · 4–8 weeks (12–16 with confirmation) · Prioritised hits with predicted binding modes
At a glance
- Price band
- USD 35–95K
- Duration
- 4–8 weeks
- With confirmation
- 12–16 weeks
- Deliverable
- Prioritised hit list
Indicative list price. Final scope and price confirmed in the proposal.
Talk to a scientistThe problem
Why teams buy this
Physical high-throughput screening is expensive and slow. Naive computational screening is neither - but it returns hits that fail immediately at the bench, which is worse than no hits at all, because you paid for the disappointment twice.
What you get
Deliverables, not activity
- A prioritised, diversity-selected hit list with predicted binding modes
- The full screening methodology and parameter record
- A compound sourcing plan with availability and cost
- Optional: confirmatory biochemical or cell-based assay results
How it works
The sequence
- 01
Target structure preparation or homology model building
- 02
Binding-site and pharmacophore definition
- 03
Library filtering and a staged screening cascade
- 04
Consensus rescoring and diversity selection
- 05
Compound sourcing and in-vitro confirmation
Who this is for
Biotech without screening infrastructure · pharma discovery teams needing extra capacity · academic drug-discovery centres.
Proof
Representative result
Six million commercially available compounds screened against a kinase target, delivering 120 diversity-selected hits, of which 14 confirmed activity in a biochemical assay.
Representative programme - illustrates typical scope and outcomes; not an individual client account. Client-specific references are available on request under confidentiality.
Questions we get asked
The awkward ones, answered
Which libraries do you screen?
Commercially available make-on-demand and in-stock libraries, plus your proprietary collection if you have one. We agree the library before we start.
What hit rate should we expect?
It depends entirely on target tractability. We will give you an honest expectation at the consultation rather than an impressive one.
Enterprise AI for Life Sciences
Ready to Advance Your Drug Discovery Pipeline?
Partner with Prognica Labs to leverage enterprise-grade AI, computational chemistry, and molecular simulation technologies that accelerate discovery, reduce development risk, and improve R&D productivity.
From biotech startups to global pharmaceutical organizations, we help research teams make faster, evidence-driven decisions across every stage of early drug discovery.