聪 刘

Led core bioinformatics tasks across the drug development pipeline: disease model construction, target discovery & validation,MoA analysis, PD marker / biomarker screening; participated in clinical study protocol design and in vivo/in vitro experimental design. Deeply involved in full-cycle bioinformatics support (PCC → preclinical → IND → Phase I) for pulmonary disease programs(IPF, COPD, chronic cough); integrated in vivo/in vitro data with clinical sequencing and CRF data to support PD markeranalysis, efficacy/safety evaluation, and patient stratification.

Integrated GWAS, TCGA, GEO, and internal data for early-stage target validation; assessed target potential across tissue (Bulk RNA-seq), single-cell (scRNA-seq), and genetic levels; developed Shiny Apps and automated HTML reporting systems, standardizing multi-dimensional target assessment workflows. Performed multi-omics integration (RNA-seq + proteomics) to elucidate drug MOA and identify PD markers; conducted patient stratification on large clinical cohorts; developed custom transcript quantification scripts to precisely calculate isoform expression ratios, directly informing project decisions. Independently developed and deployed 5 Shiny applications for internal sequencing data management; built a high-quality autoimmune disease multi-omics knowledge base by systematically re-analyzing bulk RNA-seq (33 studies) and scRNA-seq (16 studies) from public literature.

Conducted multi-omics (transcriptomics, proteomics, genomics) MoA and PD marker studies for novel drugs (molecular glues, PROTACs, ADCs); performed target exploration and validation for immuno-oncology and androgenetic alopecia indications, leveraging DepMap for cell line sensitivity analysis. Led Phase I/II/III clinical data analysis for multiple trials (COVID-19, prostate cancer, breast cancer, androgenetic alopecia), covering primary/secondary endpoints, subgroup/covariate analyses, multi-omics biomarker integration, and predictive modeling (lasso / logistic / Cox); developed automated R-based statistical reporting pipelines. Developed a high-throughput IC50 calculation system (batch CGT data processing), PK-NCA/PopPK analysis tools, and MCP-Mod for Phase III sample size estimation; established departmental data analysis SOPs and reusable analytical modules; provided team technical training.