Eladio Márquez

About Eladio Márquez

Computational biologist with 16+ years of post-graduate experience covering an array of academic and industry positions in biomedical and related fields, including, most recently, leading a translational data science team tasked with (1) identifying potential biomarkers from phase I/II clinical data from two immuno-oncology trials,(2) analyzing public and internal data to support critical IND-enabling activities for multiple clinical candidates in the I&I space, and (3) buildout the technological stack to mine single-cell expression and genetic data to discover patient populations likely to receive benefit from drugs under development.Proven record of translating multimodal data into real-world assets, with a focus on transparency and simplification to facilitate stakeholder inclusion and empower decision-making. Areas of expertise span genomics, genetics, statistics, bioinformatics, spatial biology, immunology, oncology, and others, having assumed both leading and contributor roles. Published contributions include innovative approaches and influential discoveries in spatial analysis, GWAS, immuno-aging, genomics, immuno-oncology, and translational medicine.

Experience

1. Associate Director Clinical Data Intelligence

   Hifibio Therapeutics

   Jan 2024 — Present · Cambridge, MA, US

   Directed the translational data science team, with a total of six direct reports in US and China including interns, junior, and senior members, comprising both data analysts and ML/AI engineers, spearheading a dual-mandate mission to infer predictive and prognostic biomarkers from early-stage immuno-oncology clinical trials and building the research tech stack to support IND applications for multiple drug candidates in the I&I therapeutic area• Led translational analyses of single-cell expression, BCR/TCR clonality, digital pathology, and spatial proteomics, in the context of biomarker discovery, indication selection, and patient stratification for IO and I&I clinical programs• Developed broad-scale multi-modal approaches for identification of pathogenic cell populations and construction of disease causal hypotheses to aid in indication prioritization for clinical trials in the I&I space• Developed methods for inference of PD and response biomarkers from multi-modal Phase 1 clinical data, including spatial, radiographic, and expression data• Led the integration of LLM and Foundation Models for workflows used to build an scRNA-seq database, including semi-automated metadata harmonization, cell typing, and expression normalization• Led the development of databases and analytical tools integrating genetic and single-cell data to investigate the causal role of specific cell populations in I&I diseases• Supported deal-making efforts by BD functions with clinical data analyses and insights• Worked with research functions to facilitate translational and IND-enabling activities• Relevant publications: o Predictive and generative AI to guide the clinical development of HFB200301, a first-in-class TNFR2 agonist, SITC 2024 o Evaluation of HVEM and PDL1 expression profile in tumors as potential predictive biomarkers for HFB200603, a BTLA antagonist, as monotherapy and in combination with tislelizumab, ESMO 2025

Education

• University of Michigan

  Doctor of Philosophy - PhD, Ecology and Evolutionary Biology

  2009

• Universidad Simón Bolívar

  Licentiate degree, Ecology, Evolution, Systematics, and Population Biology

  1997