Clinical interpretation of genetic data is a complex process, which involves connecting patient’s genetic variants and phenotypes with experimental scientific information. Blueprint Genetics is applying Artificial Intelligence (AI) in clinical interpretation to automate manually laborious interpretation processes and empower geneticists and clinicians to interpret patients’ test data accurately and consistently.
In this podcast, Massimiliano Gentile, Informatics Director, Ph.D. and Samuel Myllykangas, CTO, Ph.D, are discussing artificial intelligence in genetic testing of inherited disorders.
Key learning objectives:
- Why AI is instrumental in advancing the interpretation of genetic testing data
- How AI is applied for genetic testing of inherited disorders
- What AI solutions Blueprint Genetics is offering for patients today and in the future to maximise the clinical impact and actionability from genetic testing of inherited disorders.
Samuel is the chief strategy officer at Blueprint Genetics as well as a co-founder of the company. He is an expert in genome analysis technologies and has extensive experience in bioinformatics and cancer genomics research. Samuel received his PhD from the University of Helsinki and completed his postdoctoral research at Stanford University. At Stanford, he developed high-throughput sequencing technologies such as Oligonucleotide-Selective Sequencing (OS-Seq™). He is an adjunct professor in genetics at the University of Helsinki, an author of several high-impact publications, and an inventor and patent holder of DNA sequencing methods.
Massimiliano Gentile is Bioinformatics Director at Blueprint Genetics. He has vast experience in bioinformatics, especially in analysis of biological data from high throughput laboratory technologies, as well as in development of software and analysis pipelines. Upon completion of his PhD studies in cancer genetics at the University of Linköping, Sweden, he pursued post-doctoral studies in functional genomics at the University of Helsinki, Finland. He then joined the Bioinformatics Unit at the medical research institute Biomedicum Helsinki, analysing and developing methods for data analysis of data from microarray and next generation sequencing technologies.