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Evolutionary acceleration of drug development with AI
Without changing your process, we add an in silico layer: within months we find strong candidates, speed up 3D checks, and send only the best to the lab—saving budget and 3-5 years at the start.
How the process works
The process is built with a focus on quality and safety, so the first steps take time and require significant resources.
What do we offer?
We add an in silico add-on to your LIMS/ELN and SOP. AI screens millions of molecules, accelerates tertiary structure/binding estimation, docking, and basic ADMET, forming a clear shortlist for the lab.
You will get
The lab focuses on the strongest options; budget savings and 3–5 years off development, a faster path to in vitro / in vivo, full compatibility and reporting.
Request a pilot
Contact
Contact
Become a partner
Become a partner
How the process works today and why it takes time
Multi-stage checks, reproducibility, and statistical significance. Better to take longer than risk the patient.
Safety and evidence
Up front there are millions of molecule and target options. Thorough selection takes time to avoid missing a workable solution.
Many hypotheses at the start
Compliance with standards (SOP, GxP), quality control, and trace auditing. This adds steps but ensures trust in the result.
Regulatory requirements and documentation
Biology, chemistry, clinic, IT, and instrument queues. Approvals and planning affect timelines.
Coordination of teams and resources
What MolecuLink.ai does
Orchestration of AI models
Synergy
We narrow the multi-million search space to a short list of strong candidates for the lab.
Candidate filtering
Integration with your LIMS/ELN and SOP—an overlay on the existing pipeline.
Successful integration
Roles and permissions, encryption, and report formats aligned to your regulations. The pilot launches without stopping your current work.
Security and control
Security
We accelerate predictions of protein tertiary 3D structures and binding assessments.
Prediction acceleration
Speed
We orchestrate multiple models: analyze many variants and help find strong drug candidates faster.
Selection
Compatibility
Why MolecuLink in numbers
Who our solution is for:
Х10
faster
We speed up initial in silico candidate selection (compared with manual screening and classic flows).
40+
days to launch
We launch a pilot without stopping work: KPI alignment, integration, first shortlist and reports.
1+
week of integration
Connection to LIMS/ELN and SOP via API/CSV, roles/access and encryption-per your regulations.
We accelerate existing pipelines without breaking processes: fewer “empty” experiments, faster to in vitro / in vivo.
For pharma corporations
Fast shortlist for selected targets: budget savings in early stages and clear investor-ready reports.
For biotech startups
Support for personalized approaches: selecting targets and candidates for a patient/disease profile.
For medical centers
How does it work?
Our work is based on a scientific breakthrough recognized by the 2024 Nobel Prize in Chemistry, when AI first achieved over 90% accuracy in predicting 3D protein structures.
Why you can trust us
We work as an evolutionary add-on: an in silico layer that connects to your LIMS/ELN and SOP—we’re an integration, not a replacement. All predictions come with quality criteria and are confirmed in wet-lab experiments. You get transparent reports: 3D structures/binding, basic ADMET, and clear candidate priorities. Data are protected: roles and access, encryption, and reporting per your regulations.
Our mission
Make personalized medicine a reality by uniting artificial intelligence and biotechnology.
Screening AI (DNA analysis)
What we do: analyze DNA/omics, identify risk zones and targets. Result: a list of priority targets for the diagnosis/patient profile.
01
Pre-emptive Modeling AI (candidate proteins)
What we do: model candidate proteins considering genetics and biological context.
Result: a validated 3D conformation and a set of promising proteins for the task.
Result: a validated 3D conformation and a set of promising proteins for the task.
02
Therapeutic AI (drug molecules)
What we do: generate and rank molecules for selected targets; docking and basic ADMET.
Result: a short shortlist of the strongest candidates for the lab.
Result: a short shortlist of the strongest candidates for the lab.
03
Become our partner
PHONE
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COMPANY ADDRESS
Moscow, Vozdvizhenka 7/6с1
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What this means in practice:
We carefully transfer these advances to the stage of computer-aided search and design of candidate molecules (in silico), strengthening your current process.
We determine molecular shape and properties earlier and more accurately so that only strong candidates reach the lab.
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Станьте нашим партнёром и вместе мы сократим сроки разработки, откроем новые виды терапии и сделаем персонализированные лекарства доступными пациентам по всему миру.
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