Mehreen. Soomro
Clinical Data Scientist @Nweh
Signup · Get unlimited contacts
WORK HISTORY
Clinical Data Scientist @Nweh
Manchester, GB
I’m starting a role as a Clinical Data Scientist at NWEH, focused on the development of regulatory-grade clinical and real-world datasets underpinning Phase I–IV clinical development.My work sits at the intersection of clinical data standards, biostatistics, and data engineering, with an emphasis on producing datasets that are audit-ready, traceable, and analytically robust. I design and maintain CDISC/SDTM-compliant data structures, ensuring end-to-end traceability from raw source data (EHR/EMR, registries, and clinical trial capture systems) through to analysis-ready outputs.A core part of my role involves transforming heterogeneous clinical data into structured evidence using controlled clinical terminologies (SNOMED CT, ICD-10, MedDRA, WHO-DD), with careful attention to semantic consistency across domains. I implement data validation, reconciliation, and quality-control workflows to ensure alignment with GCP standards, regulatory expectations, and downstream analytical requirements. This work directly supports RWD-to-RWE conversion, enabling credible safety, effectiveness, and endpoint analyses beyond traditional trial settings.Alongside standards-driven data engineering, I contribute to the controlled and appropriate application of AI and machine learning in regulated environments. This includes developing methods for automated data-quality assessment, anomaly and inconsistency detection, cohort definition, patient stratification, and early signal refinement, while maintaining full statistical transparency and clinical interpretability.All analytical and ML development is framed within regulatory constraints and clinical context, prioritising robustness, explainability, and patient impact over model complexity. Ultimately, the aim is to deliver high-integrity clinical evidence that regulators trust, clinicians can interpret, and development teams can rely on to support safer, more efficient clinical trials.
EDUCATION
The University of Manchester
Master of Science - MSc, Health Data Science
University of London
R and data Science, Data Analysis
University of Sindh
Master of Arts - MA, Economics
Mehran University of Engineering and Technology
Bachelor of Engineering - BE, Computer Technology/Computer Systems Technology
The University of Manchester
Doctor of Philosophy - PhD, Biostatistics (Machine Learning)
ABOUT MEHREEN. SOOMRO
I am a Senior Data Scientist with over four years of experience working at the intersection of machine learning, Bayesian statistics, genomics, clinical trials, and real-world health data, with a strong focus on precision medicine and translational science.My expertise lies in developing predictive and inferential models that support drug discovery, biomarker identification, patient stratification, and treatment-response prediction. I have extensive experience working with GWAS, multi-omic, EHR/EMR, and clinical trial datasets, translating complex biological and clinical data into actionable insights that inform therapeutic development and study design.At C4X Discovery, I played a leading role in the development of PatientSeek, a genetics-led platform for predicting treatment response and enabling precision-medicine trial strategies. I also architected Taxonomy3, a scalable pipeline applying Bayesian machine learning to integrate genetic, multi-omic, and clinical data for target discovery and validation. This work directly supported novel drug-target identification, biomarker development, internal IP generation, and early drug-discovery programmes, helping accelerate the path from data to therapeutic impact.I have led analyses using large-scale IBD Plexus and NHS EHR datasets, advancing understanding of treatment outcomes in Crohn’s disease and ulcerative colitis, as well as broader applications across immunology, inflammatory disease, and chronic conditions. This breadth has strengthened my ability to model longitudinal, high-dimensional health data, where heterogeneity and temporal structure are key challenges.I am now a Clinical Data Scientist at NWEH, where I focus on developing regulatory-grade clinical and real-world datasets supporting Phase I–IV clinical development. My work includes CDISC/SDTM-compliant data structures, controlled terminologies (SNOMED CT, ICD-10, MedDRA, WHO-DD), and GCP-aligned validation and QC frameworks, as well as contributing to RWD-to-RWE conversion, trial readiness, and the controlled application of AI and machine learning in regulated environments.I hold a PhD in Biostatistics and a strong record of peer-reviewed publications and cross-sector collaboration across biotech, academia, and the NHS. I thrive in mission-driven teams where rigorous data science accelerates drug discovery, improves clinical trials, and ultimately enhances patient outcomes.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.