Licensed candidate programs · TRL 7/8
Each program below is delivered as a TRL 7/8 late-stage package – a ready-to-license blueprint that your R&D, regulatory and marketing teams can internalize and scale into differentiated products.
Engineered creatine program for high-intensity strength, power and repeated-effort performance.
Extended-release butyrate-centric program for gut barrier integrity and metabolic resilience.
Next-generation HMB + fatty-acid synergy program for lean mass preservation and recovery.
Scalp & follicular extracellular-matrix program for hair density, quality and longevity claims.
A cross-functional ecosystem of technical-educational and licensing-ready programs for teams that need auditable, scientifically grounded decisions from biological hypothesis to portfolio governance.
We support candidate programs and innovation projects from TRL 1 to TRL 8 in the classical TRL 1–9 scale: from basic principles and concept formulation through experimental proof-of-concept, lab validation, pilots, prototypes and qualified systems.
Within this range, we help you transform early scientific signals into a structured, auditable development path – mapping hypotheses, variables, biomarkers, endpoints and risk–benefit assumptions so your internal R&D, clinical, regulatory and commercial teams can move faster and de-risk decisions on the way to TRL 9 and full market deployment.
In silico discovery powered by Q-REVEL+ establishes a new benchmark in molecular precision and deep learning–driven exploration, accelerating innovation by up to 100× across aesthetics, cosmetics, rare diseases, neurodegenerative disorders and beyond.
Deep learning–driven pipelines that refine bioactive candidates at molecular resolution, focusing on relevant interactions instead of brute-force exploration.
Up to 100× faster discovery cycles, compressing exploratory timelines and reducing the cost of reaching validated shortlists for downstream development.
A single methodology spanning aesthetics, cosmetics, rare diseases, neurodegenerative disorders and more, with configurable constraints and context-specific targets.
Workflows tuned to outperform traditional high-performance computing approaches in atomic-level evaluation, prioritizing candidates with clear mechanistic rationale.
Search strategies designed to escape local optima, combining speed with novelty to strengthen differentiation, patentability and long-term portfolio value.
Q-REVEL+ allows startups, biotechs and innovation teams to operate with a discovery framework that is both computationally advanced and operationally usable. It connects molecular precision, transparent decision trails and portfolio thinking, enabling the design of cosmetic and therapeutic candidates with higher signal and lower exploratory waste.
From a single input to explainable, auditable decisions: microenvironment-first reasoning, conditional activation (AND gates), candidate generation, docking/MD consensus, reinforced ADMET/Tox, barriers & solutions, multicriteria idealness, L9 plan, minimal synthesis, executive report, audit, and ≥30 references.
Context-before-target: pH, ROS, proteases, efflux and trafficking drive AND/OR/NOT gates (τ thresholds, ton/toff) for subcellular selectivity.
3–5 candidates (SMILES) with pairing rationale and modular design (e.g., trig_pH, trig_ROS, anchor_TPP, linkers, constraints) to match the microenvironment.
Multiple scoring functions plus MD stability (RMSD/occupancy) aggregated via simple consensus; report approximate Kd (nM) and subcellular A/E metrics.
Risk flags (hERG, P-gp, Ames, DILI), PPB%, clearance and mitigations inform safety and PK subscores with transparent penalties and notes.
Multicriteria decision matrix (weights for safety/efficacy/PK/novelty/synthesis/selectivity) plus GAI/CSI gates; Taguchi L9 for fast robustness scans.
Minimal route briefing (2–5 steps), EHS and scale-up notes; one executive report with audit trail and ≥30 field references.
