Curriculum Vitae

Author

Nelson Kibinge

Published

October 20, 2026

Translational Medicine · Bioinformatics · Immuno-oncology

Nelson Kibinge, PhD

I turn patient and pre clinical data into actionable insight for oncology drug discovery from indication selection and biomarker discovery to AI-leveragingtarget prioritization.

Nelson Kibinge

Overview

Computational biologist and senior scientist at Orion Pharma in Translational Medicine, supporting oncology research across pre-clinical and clinical programmes. Recent work focuses on immuno-oncology, translational bioinformatics, and using patient molecular data to inform therapeutic development.

Current focus and capabilities

Support clinical indication selection and translational decisions by integrating disease biology with clinical and molecular evidence.
Discover and assess biomarker hypotheses using patient DNA-seq, ctDNA, and RNA-seq, including immune and tumour-related features.
Develop R and Python tools and Shiny applications; apply AI-driven approaches to oncology target discovery and prioritization.
Bring expertise in multi-omics, single-cell and spatial analysis, and cross-functional collaboration across translational, clinical, and research teams.

Earlier work spans statistical genomics at the University of Bristol and infectious-disease genomics at the KEMRI-Wellcome Trust Research Programme. He also holds an Adjunct Faculty position at Pwani University, Kenya.

Career overview

2008 BSc in Biology University of Nairobi

2011 MSc studies Nara Institute of Science and Technology

2013–2015 PhD studies Nara Institute of Science and Technology

2016–2019 Postdoctoral research KEMRI-Wellcome Trust Research Programme

2019–2020 Statistical genomics University of Bristol

2020–Present Senior Scientist Orion Pharma

Employment & experience

Feb 2020 – Present
Turku, Finland

Senior Scientist – Computational Biologist

Orion Pharma

Supports Translational Medicine and oncology research and development across pre-clinical and clinical projects. Develops and applies computational approaches to high-throughput omics data, contributes to drug-target prioritization and biomarker discovery, and collaborates with academic groups on data-driven bioinformatics and AI.

Apr 2019 – Jan 2020
Bristol, United Kingdom

Senior Research Associate – Statistical Genomics

MRC Integrative Epidemiology Unit, University of Bristol

Applied genomics and epidemiology methods to identify therapeutic targets for autoimmune diseases, communicated scientific findings, and facilitated academic–pharma collaboration.

Jan 2019 – Mar 2019
Heidelberg, Germany

Visiting Research Scientist

Heidelberg University

Developed statistical methods for analysis of KILchip Protein Microarray data.

Mar 2018 – Jun 2019
Kilifi, Kenya

Senior Postdoctoral Scientist – Acting Head of Statistics

KEMRI-Wellcome Trust Research Programme

Led the statistics unit, supported institutional statistical needs, and developed statistical methods for diverse omics datasets.

Mar 2016 – Nov 2018
Kilifi, Kenya

Early Career Postdoctoral Scientist

KEMRI-Wellcome Trust Research Programme

Conducted research on malaria and virus genomics and diversity in long-term surveillance; wrote and published research; and supervised master’s students and interns.

Jul 2016 – Present
Kilifi, Kenya

Adjunct Faculty

Pwani University

Taught MSc Bioinformatics courses in biostatistics, data science for biology, databases, and data visualization; examines master’s and doctoral theses in bioinformatics.

Mar 2015 – Sep 2015
Niigata, Japan

Bioinformatics Intern

Yukiguni Maitake

Developed transcriptomics and genomics software tools supporting research and development in Maitake mushroom cultivation.

2008 – 2009
Kenya

Medical Sales Representative

Pharmaken Kenya Ltd.

Marketed generic anti-inflammatory and analgesic products in Nairobi and the North Eastern region.

Education

2013–2015

PhD in Computational Biology

Nara Institute of Science and Technology (NAIST)

View doctoral thesis

Integrated pathway-based transcription regulation network mining to decipher the role of transcription factors in the heterogeneity of small cell lung cancer phenotypes.

2011–2013

MSc in Computational Biology

Nara Institute of Science and Technology (NAIST)

View master’s thesis

Protein sequence diversity characterization using the physical attributes of amino acids: Examples in Plasmodium falciparum sequences and terpenoid enzymes.

2010–2011

Intensive Japanese Language Course

Osaka University

2004–2008

BSc in Biology

University of Nairobi

1999–2002

Secondary Education

St Patrick’s High School, Iten

Research & technical areas

Translational oncology bioinformatics

Current focus — Translational Medicine, Orion Pharma

Support pre-clinical and clinical oncology programmes, with recent work primarily in immuno-oncology bioinformatics.
Support clinical-project indication selection by integrating available molecular and clinical evidence to characterize disease biology, patient subgroups, and translational rationale.
Integrate genomic, transcriptomic, proteomic, single-cell, and spatial data to characterize tumour and immune biology and generate testable hypotheses.
Contribute computational evidence for target discovery and validation, target confidence, biomarker development, and patient stratification.
Translate analyses into clear evidence and decision support for multidisciplinary project teams.

Immuno-oncology bioinformatics

Analyze molecular and high-throughput data to investigate tumour–immune interactions and the tumour microenvironment.
Support characterization of immune-cell populations, immune-related molecular signatures, and variation across tumour samples or patient groups.
Connect pre-clinical and clinical evidence to translational questions around target biology, biomarkers, and patient stratification.
Apply single-cell and spatial approaches where data are available to add cellular and tissue context to oncology findings.
Discover and evaluate biomarker hypotheses using patient DNA sequencing, circulating tumour DNA (ctDNA), and RNA sequencing data, applying fit-for-purpose contemporary computational and statistical methods.
Support multi-modal interpretation of patient-derived data, including somatic variant and genomic feature characterization, RNA expression signatures, and longitudinal ctDNA signal assessment when relevant to study design and data availability.
Contribute to immuno-oncology target research, including work on CBL-B in tumour-infiltrating immune cells, presented at AACR 2025.

Core competencies

Translational medicine: connect discovery and clinical evidence; frame answerable questions; interpret findings in biological and programme context.
Omics and bioinformatics: high-throughput data analysis across genomics, transcriptomics, proteomics, and single-cell and spatial modalities.
Immuno-oncology: tumour–immune biology, immune-cell profiling, tumour-infiltrating immune cells, and immune-related signatures.
Biomarkers and precision oncology: support biomarker hypotheses, molecular subgroups, and patient-selection strategies.
Statistical genomics: GWAS, genetic epidemiology, Mendelian randomization, and proteomic-data analysis.

Modern pharmaceutical data science

R and Python tool development: develop analytical tools, reusable workflows, and data-science applications to support research and development questions, omics analysis, and scientific decision-making.
AI-driven drug discovery: apply AI and machine-learning approaches to support oncology target discovery and prioritization, target-confidence assessment, and data-driven hypothesis generation.
Reproducible analytics: build fit-for-purpose, documented workflows with attention to data provenance, quality, and reviewability.
Evidence-aware interpretation: account for study design, cohort composition, data limitations, and uncertainty; distinguish exploratory signals from validated findings.
Cross-functional delivery: collaborate with clinical, translational, computational, and experimental colleagues; communicate results for both technical and non-technical audiences.
Responsible use of advanced methods: select methods appropriate to the question and data, with transparent assumptions and suitable validation.

Broader research experience

Statistical genomics and genetic epidemiology for therapeutic target prioritization.
Malaria and viral genomics, long-term surveillance, host immunity, and infectious-disease research.
Bioinformatics across genomics, transcriptomics, and proteomics, with experience communicating and publishing collaborative research.

Selected publications

Abstract 914: Differential expression of Cbl-b in tumor infiltrating immune cells in patients with solid tumors. Elli Narvi, Reetta Virtakoivu, Endrit Elbasani, Nelson Kibinge, Laura Ravanti, and Anil K. Thotakura (2025). Cancer Research, 85(8 Supplement 1), 914. Presented at the American Association for Cancer Research (AACR) Annual Meeting. Abstract · DOI

Correlation of laboratory safety variables with disease course in the REFALS phase 3 study of levosimendan in people with ALS (4125). Nelson Kibinge, Alex Dickens, Angela Genge, Nicholas Maragakis, Susanne Petri, Leonard Van den Berg, Ammar Al-Chalabi, Valtteri Aho, Kira Holmström, and Merit Cudkowicz (2021). Neurology, 96(15 supplement), 4125. Abstract

Characterizing the causal pathway for genetic variants associated with neurological phenotypes using human brain-derived proteome data. Nelson K. Kibinge, Caroline L. Relton, Tom R. Gaunt, and Tom G. Richardson (2020). The American Journal of Human Genetics, 106(6), 885–892. Article · Google Scholar

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles. Nelson Kibinge, N. Ono, M. Horie, T. Sato, T. Sugiura, M. Altaf-Ul-Amin, et al. (2016). Journal of Biomedical Informatics, 61, 194–202. Google Scholar

See other publications

Biomarkers of post-discharge mortality among children with complicated severe acute malnutrition. J. M. Njunge, A. Gwela, N. K. Kibinge, et al. (2019). Scientific Reports, 9, 5981. Scholar
Data mining methods for omics and knowledge of crude medicinal plants toward big data biology. F. M. Afendi, N. Ono, Y. Nakamura, K. Nakamura, L. K. Darusman, N. Kibinge, et al. (2014). Scholar
Controlled Human Malaria Infection in Semi-Immune Kenyan Adults (CHMI-SIKA): a study protocol to investigate in vivo Plasmodium falciparum malaria parasite growth in the context of pre-existing immunity. M. C. Kapulu, P. Njuguna, M. M. Hamaluba, CHMI-SIKA Study Team (2019). Wellcome Open Research, 3, 155. Article · Scholar
Controlled Human Malaria Infection in Semi-Immune Kenyan Adults (CHMI-SIKA): a study protocol… M. C. Kapulu, P. Njuguna, M. M. Hamaluba, CHMI-SIKA Study Team (2019). Additional Google Scholar record for the protocol. Scholar
KILchip v1.0: A novel Plasmodium falciparum merozoite protein microarray to facilitate malaria vaccine candidate prioritization. G. Kamuyu, J. Tuju, R. Kimathi, K. Mwai, J. Mburu, N. Kibinge, et al. (2018). Frontiers in Immunology, 9, 2866. Article · Scholar
Anti-merozoite antibodies induce natural killer cell effector function and are associated with immunity against malaria. D. Odera, J. Tuju, K. Mwai, et al., including N. Kibinge (2023). Science Translational Medicine, 15(682), eabn5993. Article · Scholar
Distinct kinetics of antibodies to 111 Plasmodium falciparum proteins identifies markers of recent malaria exposure. V. Yman, J. Tuju, M. T. White, et al., including N. Kibinge (2022). Nature Communications, 13, 331. Article · Scholar
Clustering of 3D-structure similarity based network of secondary metabolites reveals their relationships with biological activities. Y. Ohtana, A. A. Abdullah, M. Altaf-Ul-Amin, et al. (2014). Molecular Informatics, 33(11–12), 790–801. Scholar
Molecular epidemiology of human rhinovirus from one-year surveillance within a school setting in rural coastal Kenya. M. M. Luka, E. Kamau, I. Adema, et al., including N. Kibinge (2020). Open Forum Infectious Diseases, 7(10), ofaa385. Article · Scholar
Evaluating the performance of tools used to call minority variants from whole genome short-read data. K. S. Mohammed, N. Kibinge, P. Prins, et al. (2018). Wellcome Open Research, 3, 21. Scholar
Evaluating the performance of tools used to call minority variants from whole genome short-read data (version record). K. S. Mohammed, N. Kibinge, P. Prins, et al. (2018). Scholar
Evaluating the performance of tools used to call minority variants from whole genome short-read data (version record). K. S. Mohammed, N. Kibinge, P. Prins, et al. (2018). Scholar
Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK database. S. Ikeda, T. Abe, Y. Nakamura, N. Kibinge, et al. (2013). Plant and Cell Physiology, 54(5), 711–727. Scholar
Cerebrospinal fluid markers to distinguish bacterial meningitis from cerebral malaria in children. J. M. Njunge, I. N. Oyaro, N. K. Kibinge, et al. (2017). Wellcome Open Research, 2, 47. Scholar
Breadth of antibodies to Plasmodium falciparum variant surface antigens is associated with immunity in a controlled human malaria infection study. H. W. Kimingi, A. W. Kinyua, N. A. Achieng, et al. (2022). Frontiers in Immunology, 13, 894770. Scholar
Peripheral blood mononuclear cell transcriptomes reveal an over-representation of down-regulated genes associated with immunity in HIV-exposed uninfected infants. Z. D. Musimbi, M. K. Rono, J. R. Otieno, N. Kibinge, et al. (2019). Scientific Reports, 9, 18124. Article · Scholar
protGear: A protein microarray data pre-processing suite. K. Mwai, N. Kibinge, J. Tuju, G. Kamuyu, R. Kimathi, J. Mburu, et al. (2021). Computational and Structural Biotechnology Journal. Article · Scholar
Molecular epidemiology of human rhinovirus from one-year surveillance within a school setting in rural coastal Kenya. E. Gicheru, A. Gichuki, D. J. Nokes, M. M. Luka, et al., including N. Kibinge (2020). medRxiv · Scholar
In-silico immune cell deconvolution of the airway proteomes of infants with pneumonia reveals a link between reduced airway eosinophils and an increased risk of mortality. C. J. Sande, J. M. Waeni, J. M. Njunge, et al., including N. K. Kibinge (2019). bioRxiv, 840090. Scholar
Characterization of antibody kinetics in travellers with Plasmodium falciparum infection allows for identification of serological markers of cumulative and recent malaria exposure. V. Yman, J. Tuju, M. T. White, et al., including N. Kibinge (2019). American Journal of Tropical Medicine and Hygiene, 101, 290. Scholar
Assessing the utility of minority variant composition in elucidating RSV transmission pathways. G. Githinji, C. N. Agoti, N. Kibinge, et al. (2018). bioRxiv. Scholar
Protein sequence modeling and transcription regulation network analysis towards integrative big data biology. N. K. Kibinge (2016). Nara Institute of Science and Technology. Scholar
Plasmodium phylogenetics and numeric modification of amino acid residues. N. K. Kibinge (2013). Nara Institute of Science and Technology. Scholar
Integration of residue attributes for sequence diversity characterization of terpenoid enzymes. N. Kibinge, S. Ikeda, N. Ono, M. Altaf-Ul-Amin, and S. Kanaya (2014). BioMed Research International, 2014, 753428. Scholar
Distinct kinetics in antibody responses to 111 Plasmodium falciparum antigens identifies novel serological markers of recent malaria exposure. V. Yman, J. Tuju, M. T. White, et al., including N. Kibinge (2020). medRxiv. Scholar
RSV modelling meeting. K. Atkins, M. Baguelin, S. Brand, et al., including N. Kibinge (2017). Meeting record, University of Warwick. Scholar
Fall-risk classification of the timed up-and-go test with principal component analysis. N. Tanaka, N. A. Zakaria, N. K. Kibinge, et al. (2014). International Journal of Neurorehabilitation, 1, e106. Scholar
The landscape of paediatric infectious disease exposure in a rural sub-Saharan Africa setting in Kilifi, Kenya: longitudinal serological analysis over two decades and priorities for future vaccine development. D. F. Foley, T. K. Chege, J. Kabagenyi, et al., including N. Kibinge (2024). medRxiv. Scholar record

Enabling tools & workflows developed

Selected examples of Shiny-based bioinformatics applications developed for interactive exploration of omics and screening data. The images below are illustrative mockups, not screenshots of the live applications; they contain no real study data.

Single-cell explorer

Interactive exploration of single-cell datasets, with visual summaries to support review of cellular populations, marker patterns, and sample-level variation.

Format: Shiny-based application · Image: illustrative mockup

RNA-seq explorer

Interactive review of RNA-seq results, designed to help browse expression patterns, compare contrasts, and inspect candidate genes and pathway-level summaries.

Format: Shiny-based application · Image: illustrative mockup

CRISPR screening target-discovery app

Interactive analysis of CRISPR screening outputs to support screen review, prioritization of candidate targets, and follow-up investigation.

Format: Shiny-based application · Image: illustrative mockup

Awards & achievements

2025 Orion Innovation Award — Development of an in-house oncology single-cell explorer platform, deployed in production for target discovery and ideation.

2010 Monbukagakusho (MEXT) Scholarship — Awarded to pursue master’s and doctoral studies in bioinformatics.

2008 Gandhi Smarak Nidhi Fund Prize — Top graduate student, School of Biological Sciences, University of Nairobi, Class of 2008.

Contact

For professional inquiries, contact nelkibs@gmail.com, or connect via LinkedIn and Google Scholar.