Development of informatic tools for extracting biomedical data from open and propietary data sources with predictive purposes

López Massaguer, Oriol

Development of informatic tools for extracting biomedical data from open and propietary data sources with predictive purposes

Document Type

Doctoral thesis
Published Version

Author

López Massaguer, Oriol

Director

Pastor Maeso, Manuel

Publication Date

2017-12-14

Pages

179 p.

Citation

López Massaguer, O. Development of informatic tools for extracting biomedical data from open and propietary data sources with predictive purposes. Universitat Pompeu Fabra; 2017. handle: http://hdl.handle.net/10803/471540

This citation was generated automatically.

Doctoral program

Programa de doctorat en Biomedicina

Abstract

Hem desenvolupat noves eines de software per tal d’obtenir informació de fonts publiques i privades per tal de desenvolupar models de toxicitat in silico. La primera eina es Collector, una aplicació de programari lliure que genera series de compostos preparats per fer modelat QSAR anotats amb bioactivitats extretes de la plataforma Open PHACTS usant tecnologies de la web semàntica. Collector ha estat utilitzada dins el projecte eTOX per desenvolupar models predictius sobre endpoints de toxicitat. Addicionalment hem concebut, desenvolupat i implementat un mètode per derivar scorings de toxicitat apropiats per modelatge predictiu que utilitza les dades obtingudes de informes d’estudis amb dosis repetides in vivo de la industria farmacèutica. El nostre mètode ha estat testejant aplicant-lo al modelat de hepatotoxicitat obtenint les dades corresponents per 3 endpoints: ‘degenerative lesions’, ‘inflammatory liver changes’ and ‘non-neoplasic proliferative lesions’. S’ha validat la idoneïtat d’aquestes dades obtingudes comparant-les amb els valors de point of departure obtinguts experimentalment i també desenvolupant models QSAR de prova obtenint resultats acceptables. El nostre mètode es basa en la inferència basada en ontologies per extreure informació de la nostra base de dades on tenim dades anotades basades en ontologies. El nostre mètode també es pot aplicar a altres bases de dades amb informació preclínica per generar scorings de toxicitat. Addicionalment el nostre mètode d’inferència basat en ontologies es pot aplicar a d’altre bases de dades relacionals anotades amb ontologies.
We developed new software tools to obtain information from public and private data sources to develop in silico toxicity models. The first of these tools is Collector, an Open Source application that generates “QSAR-ready” series of compounds annotated with bioactivities, extracting the data from the Open PHACTS platform using semantic web technologies. Collector was applied in the framework of the eTOX project to develop predictive models for toxicity endpoints. Additionally, we conceived, designed, implemented and tested a method to derive toxicity scorings suitable for predictive modelling starting from in vivo preclinical repeated-dose studies generated by the pharmaceutical industry. This approach was tested by generating scorings for three hepatotoxicity endpoints: ‘degenerative lesions’, ‘inflammatory liver changes’ and ‘non-neoplasic proliferative lesions’. The suitability of these scores was tested by comparing them with experimentally obtained point of departure doses as well as by developing tentative QSAR models, obtaining acceptable results. Our method relies on ontology-based inference to extract information from our ontology annotated data stored in a relational database. Our method, as a whole, can be applied to other preclinical toxicity databases to generate toxicity scorings. Moreover, the ontology-based inference method on its own is applicable to any relational databases annotated with ontologies.