From evidence synthesis and data curation
to knowledge systems and discovery

To inform new research directions, decision-making and practice, we systematically identify, assess and synthesize evidence from published literature on a defined scientific or decision question using established methods and recognized reporting standards, including PRISMA and other relevant guidelines. We prepare systematic reviews, scoping reviews and other scholarly publications arising from the evidence synthesis. When applicable, we facilitate prospective protocol registration in PROSPERO and conduct the review in accordance with the registered protocol.

Extract, interpret, standardize, harmonize and organize relevant biomedical data and metadata from scientific literature, databases, ontologies, clinical notes and other authoritative sources, following recognized domain standards and project-specific guidelines where applicable. Develop structured, traceable and machine-readable datasets with appropriate provenance and quality controls, suitable for analysis, integration and development of databases, ontologies and downstream software applications. Organize and document curated data in alignment with FAIR principles to improve findability, accessibility, interoperability and reusability.

Perform precise, detailed and structured characterization of phenotypic features for each subject using standardized medical terminologies, including the Human Phenotype Ontology (HPO). Develop structured and computable phenotype profiles that can support genomic variant interpretation, diagnosis, genotype–phenotype analysis, patient stratification and precision medicine. Encode case-level phenotypic, clinical and genomic information using standards such as GA4GH Phenopackets.

Design and develop structured biomedical databases and related applications around defined scientific questions, data requirements and intended users. Determine and model relevant entities, relationships, evidence and metadata, and apply appropriate normalization and database schema design principles to build coherent, reliable, searchable and connected data resources. Support data access, integration, interoperability and downstream research workflows through web applications, APIs and other software interfaces.

Create ontologies that capture and organize domain-specific knowledge as computable concepts and relationships. Establish the scope and intended use, identify and define relevant concepts and relationships, harmonize terminology, support consistent annotation, and facilitate interoperability, data integration, semantic search and analysis across biomedical datasets and knowledge resources. Extend existing ontologies to incorporate new concepts, relationships or other domain-specific requirements while maintaining structural and semantic consistency.

Evaluate whole-genome or whole-exome sequencing-derived variant lists and prioritize genomic variants through expert interpretation of genetic, clinical and biological evidence, supported by relevant bioinformatics databases, computational tools and published literature. Evaluate each variant against the ACMG/AMP criteria and apply the corresponding classification rules to assign clinical significance. Additional bioinformatic analyses can examine potential effects on protein structure and function, biological pathways and related molecular mechanisms. Case reports and other scientific publications can also be prepared from the curated findings.

We integrate genetic, biological, functional, pharmacological, and other relevant biomedical evidence to identify, evaluate, and prioritize promising therapeutic targets for further investigation and therapeutic development. Our workflows are tailored to the disease context and support both infectious and non-infectious disease research.

We identify and evaluate opportunities to repurpose or reposition existing and previously investigated drugs for new therapeutic indications across infectious and non-infectious diseases. We integrate relevant biological, pharmacological, experimental, clinical, and published evidence to assess therapeutic potential, prioritize promising candidates, and support informed decision-making. We also design and develop custom drug repurposing databases and knowledgebases for specific diseases, therapeutic areas, or compound portfolios.