Research, freedom-to-operate, and formulation & CMC for monoclonal antibodies, bispecifics, antibody-drug conjugates, mRNA-LNP, AAV gene therapy, and cell therapies.
Drawing on approved biologics and biosimilars, antibody structures and sequences, the therapeutic pipeline, cell-line provenance, published lipid nanoparticle formulations and protein references. Candidates are framed in ICH Q5A to Q5E, Q6B, Q13 and Q14.
The three studies cover research, freedom to operate, and formulation and CMC for each of them.
Each with the question it is asked, the stages it works through, and what it hands back.
Synthesises the biologics landscape: approved products, the pipeline and the antibody references.
ICH Q5A to Q5E · Q6B · Q13Approved products · the pipeline · structures and sequences
Procedure
Records BLR-0001 onwards, numbered in your organisation’s own sequence.
Investigates approved biologics by modality, the therapeutic antibody pipeline, antibody structures and sequences, protein references and cell-line provenance, and the regulatory framework in ICH Q5A to Q5E, Q6B and Q13. Every claim links back to the registry, patent, structure or publication behind it.
What it returns
A structured synthesis in prose: the approved-product landscape, pipeline and competitive intelligence, structural and sequence references, the regulatory framework, and open questions.
“What biologics are approved against TNF-α: originators, biosimilars and interchangeables?”
Freedom to operate for antibodies, ADCs, bispecifics, LNPs, AAV and cell therapies.
Sequence similarity · patent landscape · approved precedentAntibody sequences from patents and literature · the patent corpus · cell-line provenance
Procedure
Records BFTO-0001 onwards, numbered in your organisation’s own sequence.
Maps the patent landscape by keyword and by sequence. For an antibody, submit the VH and VL sequences and it finds the closest antibody sequences disclosed in patents and literature, and the patents that claim them. It covers ADCs across all four components, bispecific formats and Fc engineering, AAV capsids and engineered variants, and LNP ionisable lipids with their helper, sterol and PEG combinations, alongside approved precedent and the clinical pipeline for the same target.
What it returns
2 to 4 design-around strategies as cards (BFTO01, BFTO02…), each with its rationale and its own risk rating of low, moderate or high.
“FTO assessment for this anti-Trop2 ADC candidate: antibody VH/VL, vc-MMAE linker-payload, cysteine conjugation.”
Designs biologic drug-product candidates for a named target.
ICH Q5C · Q6B · Q2(R2) · Q14 · Q5A(R2)Approved-label precedent · excipient precedent
Procedure
Records BCMC-0001 onwards, numbered in your organisation’s own sequence.
Covers high-concentration subcutaneous mAbs (viscosity, aggregation, immunogenicity, fill-finish), bispecific Fc-engineered formulations, ADC drug products (linker stability, payload solubility, DAR variants), LNP-mRNA (ionisable lipid choice, molar ratios, particle size and encapsulation targets), and CAR-T, AAV and cell-therapy cryopreservation. Excipients are checked against regulatory precedent and approved-product labels. Each rationale names the approved biologic it follows and tags every CMC red flag with its severity.
What it returns
2 to 4 design candidates (BF01, BF02…), each labelled with its modality, route and target: components, process, stability profile, release specifications to ICH Q6B, and safety notes.
“CMC design for a 200 mg/mL anti-IL-13 IgG4 mAb for autoinjector SC delivery.”
Research suite
Formulation, optimisation, literature review, deformulation, FTO, patent drafting, VCM process design and data analysis.
Safety suite
ERA, extractables, leachables, nitrosamines, OEL, and PDE, anchored to ICH M7, EMA HBEL, USP <1664>, and ECETOC TR 101.
Overview
What DeepC hands back, how it shows its work, and the workspace around it: the platform overview.
From a first call to a pilot on your own programme.
A call with a formulation lead, who is in touch within a business day.
On your own programme, scoped with your team.
The AI model providers behind DeepC retain none of your content and train nothing on it.
Prefer email? info@deepceutix.com