{"id":82109,"date":"2026-05-08T11:24:03","date_gmt":"2026-05-08T09:24:03","guid":{"rendered":"https:\/\/fhi.nl\/?page_id=82109"},"modified":"2026-05-08T11:26:23","modified_gmt":"2026-05-08T09:26:23","slug":"personalized-medicine-in-practice-from-data-to-decisions","status":"publish","type":"page","link":"https:\/\/fhi.nl\/en\/personalized-medicine-in-practice-from-data-to-decisions\/","title":{"rendered":"Personalized Medicine in practice: from data to decisions"},"content":{"rendered":"
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Seminar<\/h6>\n\t\t\t\t\n\t\t\t\t

\n\t\t\t\t\tPersonalized Medicine in practice: from data to decisions\t\t\t\t<\/h1>\n\n\t\t\t\t
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Personalized medicine is rapidly changing the way patients are diagnosed and treated. By translating biological and genetic data into actionable clinical insights, healthcare professionals can make more informed treatment decisions tailored to individual patients.<\/p>\n

In this seminar you will explore how data-driven approaches, including pharmacogenomics, support personalized treatment strategies in daily practice. Experts will share insights into current developments, practical challenges and future opportunities in applying personalized medicine, from laboratory data to clinical decision-making.<\/p>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n

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10.00 \u2013 10.30<\/h2><\/div>\t\t\t\t\t\t
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Not all reads are created equal:<\/strong> a comparison of pharmacogenomic testing methods<\/strong><\/p>\n

Pharmacogenomics (PGx) allows for adjusting drug treatment based on a patients individual genetic make-up. In the Netherlands, PGx testing has been standard clinical care for over a decade. However, with the rapidly increasing developments regarding genotyping technologies it becomes important to use the correct methods for the correct problems. The main technologies used for PGx testing are: Single Nucleotide Variant (SNV) panel testing, short read sequencing (SRS) and long-read sequencing (LRS). Each of these offer distinct advantages and limitations relevant to routine lab implementation.<\/p>\n

SNV panel tests are highly efficient, cost-effective and straightforward to implement. They are however limited by a predefined set of variants. SRS on the other hand can detect all variants in the target region, at the cost of increased complexity and bioinformatic requirements and limitations in genetically complex regions. Finally, LRS provides the most superior resolution of complex regions, which are common in PGx, but the costs and turn around time are a lot higher. Finally, the interpretation of PGx can be difficult and not straightforward, for this AI in the form of machine learning can help to assist humans in interpreting genetic complexity. Understanding these pros and con's of each technology for personalized medicine can help laboratories to optimize their PGx testing strategy.<\/p>\n

This presentation will discuss the three main genotyping strategies and how they apply to PGx as well as how AI can help us to better understand the genetic contribution to drug response.<\/p>\n

Speaker: Dr. Maaike van der Lee, Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center<\/em><\/p>\n\t\t<\/div>\n\t<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":41,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"branches":[14],"events":[8],"secretariat":[],"categories":[59],"themes_tax":[517],"class_list":["post-82109","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nPersonalized Medicine in practice: from data to decisions - FHI, federatie van technologiebranches<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fhi.nl\/en\/personalized-medicine-in-practice-from-data-to-decisions\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Personalized Medicine in practice: from data to decisions - 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