Session 3 – Advances in Precision Medicine
Date: 25 July (Thursday) 09:00 – 12:00 Venue: 3F, Bldg. A, CTBC Financial Park, Ballroom A
Director Molecular Profiling, Translational Sciences, Early Phase Operations
Her interest in omics technologies and biomarker identification began in 2004 when she was in charge of projects for the identification and characterization of drug targets and diagnostic markers in the field of osteoporosis and chronic pain as Research Scientist at Axxam (Milan, Italy). From 2007 to 2011 she served as Scientific Director for Genopolis, an Italian scientific public institution with the aim to develop, integrate and disseminate Functional Genomics to national and international research entities. In 2011, she moved to Singapore where she succeeded in setting up and running the “Functional Genomic Platform” as Group Leader and Co-PI of the “Translational medicine Immunomonitoring Platform” in SIgN, within A*Star. Francesca‘s group supported all aspects of genomics research at SIgN by providing state-of-the-art technology and technical expertise. She provided a large contribution in advancing Translational Sciences by developing and implementing protocols for DNA-seq, ChIP-seq, RNA-seq, single cell RNA-Seq, gut and saliva metagenome as well as TCR and Ig repertoires.
She recently moved back to Europe as Head of Genomics and Bioinformatics and subsequently Head of Molecular Dermatology in Nestlé Skin Health (Galderma), where she led the global strategy biomarker discovery activities (2016-2018). At Syneos Health today she proposes her knowledge and the relevant Omics platforms to help clients to advance their clinical or preclinical programs in drug development. Francesca obtained her bachelor’s degree in biology from the University of Padova, Italy and a postgraduate degree in Medical Genetics, University of Verona, Italy.
She has co-authored more than 50 peer reviewed papers.
Session Speech Title & Synopsis: Data Integration and Artificial Intelligence to accelerate Precision Medicine in the Clinic
In the past 20 years, as a consequence of the Human Genome Project, we have observed an exponential growth in the amount of omics data that the scientific community is producing. The prediction that Francis Collins published in 1999 in a foundational document of precision medicine described the way human genome sequencing would have been used to predict, prevent, and treat disease in 2010. These expectations, nevertheless, have still not been met nearly ten years later.
The most promising research in the field of precision medicine is characterized by sustained collaboration across disciplines and the use of data integration and Artificial Intelligence-based (AI) algorithms to combine medicine, biology, statistics and computing.
With the rapid progress in data integration and machine learning algorithms, AI is gradually entering the clinic to enable better diagnosis, disease surveillance and prevention. In order to accelerate precision medicine in the clinic, Syneos Health now provides integrated solutions in Translational Sciences, including comprehensive molecular profiling facilities that incorporate genomics, transcriptomics, proteomics, metabolomics, molecular histology and data analysis solutions, that can help refine disease knowledge based on molecular biomarkers.
I will provide several examples of the use of AI to define patient stratification based on omics data and a case study of a phase II trial, where exploratory measurements were combined with clinical scores and clinical laboratory data and processed using unsupervised machine learning algorithms. Our analyses were able to define several subsets of patients with different molecular and clinical response profiles which can now be used to better stratify patients, or adjust the therapy as required to improve the response to treatment.