Biographical Sketch

NAME: Ibon Martínez Arranz

POSITION TITLE: Data Science Manager at Rubió Metabolomics

EDUCATION/TRAINING:

INSTITUTION AND LOCATION	DEGREE	COMPLETION DATE	FIELD OF STUDY
University of Basque Country (UPV/EHU) (Biscay, Spain)	BSc.	June 2003	Mathematics
National University of Distance Education (Spain)	Expert degree	July 2007	Statistics Applied to Health Sciences
National University of Distance Education (Spain)	Expert degree	July 2008	Advanced Methods of Applied Statistics
National University of Distance Education (Spain)	MSc.	July 2012	Current Applied Statistics Techniques
National University of Distance Education (Spain)	Expert degree	July 2013	Multivariate Statistical Techniques
University of Basque Country (UPV/EHU) (Biscay, Spain)	MSc.	May 2016	Mathematical Modeling, Statistical Analysis and Computation
University of basque Country (UPV/EHU) (Biscay, Spain)	PhD.	June 2025	Applied Mathematics

I have completed a doctoral thesis entitled “Genetic Algorithms Applied to Translational Strategy in MASH. Learning from Mouse Models”, carried out under the supervision of José María Mato (General Director of CIC bioGUNE) and Dae-Jin Lee (Data Science line leader at the Basque Center for Applied Mathematics, BCAM). In this work, I applied genetic algorithms to identify subtypes of NAFLD based on metabolic features. The methodology developed can be extended to other diseases characterized by metabolic alterations, offering promising applications in the field of precision medicine.

A. Personal Statement

Dr. Ibon Martínez-Arranz, PhD, got his BSc. in Mathematics from the University of the Basque Country (EHU/UPV) and completed an MSc. in Current Applied Statistics Techniques and an MSc. in Mathematical Modeling Research, Statistical Analysis and Computing Sciences. In 2004, he joined the Basque Country Health Service (The Department of Health of the Basque Country Government and Osakidetza) as a data analyst, focusing primarily on epidemiological reporting for renal patients. When he joined OWL Metabolomics in 2010, Ibon first worked as a researcher in the Metabolomics Department, and in 2017, he became the Head of the Data Science Department, being responsible for predictive modeling and statistical computing. His highly experienced team supports metabolomics services, laboratory processes, data handling, R&D projects, and technology transfer processes.

B. Positions and Honors

Head of Data Science Department at Rubió Metabolomics. (2023 - to date). Head of Data Science Department at OWL Metabolomics. (2017 - 2023). Researcher in Metabolomics Department at OWL Metabolomics. (2010 - 2017).

C. Contributions to Science

Author of 27 publications Google Scholar H-index = 19 Researcher unique identifier

• ORCID
• Scopus
• pubmed

Data mining of 'omics' data

'Omics' research generates a large amount of data for every sample. OWL has established a well-defined workflow and a set of guidelines for analyzing omics data. It includes statistical design of experiments, data structuration and predictive modelling.

Peer-reviewed papers:

1. Martínez-Arranz, I, et al. Enhancing metabolomics research through data mining, J. Proteomics, 2015;127(B)275-288.
2. Barr J, et al. Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression. J. Proteome Res 2012;11(4),2521-32
3. Arbelaiz A, et al. Serum extracellular vesicles contain protein biomarkers for primary sclerosing cholangitis and cholangiocarcinoma. Hepatology. 2017; 10.1002/hep.29291.
4. Cano A, et al. A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients. Scientific Reports. 2017;7(1):10497.

Predictive algorithms for disease diagnosis

We have developed predictive algorithms for several diseases. We have been really involved in the development and validation of the OWLiver, OWLiver F2+ and OWLiver DM2 tests.

Peer-reviewed papers:

1. Barr J, et al. Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression. J. Proteome Res. 2012;11(4):2521-32.
2. Cano A, et al. A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients. Scientific Reports. 2017;7(1):10497.
3. Herreros-Villanueva M, et al. Plasma MicroRNA Signature Validation for Early Detection of Colorectal Cancer. Clin Transl Gastroenterol. 2019 Jan;10(1).
4. Matorras R, et al. The lipidome of endometrial fluid differs between implantative and non-implantative IVF cycles. J Assist Reprod Genet. 2020;37(2):385-94.
5. Martínez-Arranz I, et al. Metabolomic-based noninvasive serum test to diagnose nonalcoholic steatohepatitis: Results from discovery and validation cohorts. Hepatol Commun. 2018 May 4;2(7):807-820.

Selected publications focused in Machine Learning and Modelling (within last 5 years)

Peer-reviewed papers:

1. Alonso C, et al. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis. Gastroenterology 2017;152(6):1449-61.
2. Iruarrizaga-Lejarreta M, et al. Role of Aramchol in steatohepatitis and fibrosis in mice. Hepatology Communications 2017;1(9):911-27.
3. Banales JM, et al. Serum metabolites as diagnostic biomarkers for cholangiocarcinoma, hepatocellular carcinoma and primary sclerosing cholangitis. Hepatology 2019;70(2):547-65.
4. Herreros-Villanueva M, et al. Plasma MicroRNA Signature Validation for Early Detection of Colorectal Cancer. Clin Transl Gastroenterol. 2019 Jan;10(1).
5. Matorras R, et al. The lipidome of endometrial fluid differs between implantative and non-implantative IVF cycles. J Assist Reprod Genet. 2020;37(2):385-94.

D. Patents Granted and Pending

PUBLICATION NUMBER	TITLE	INTERNATIONAL FILING DATE
WO2021028562	Lipid signatures for determining the outcome of embryo implantation during in vitro fertilization	14.08.2020
WO2018007511	Diagnostic methods based on lipid profiles	06.07.2017
WO2018007422	Identification of human Non-Alcoholic Fatty Liver Disease (NAFLD) subtypes	05.07.2017
WO2017055397	Metabolomic signature of diagnosis and disease progression in Non-Alcoholic Fatty Liver Disease (NAFLD)	29.09.2016