Updated: Feb 1, 2021
Traditional drug discovery research is based on a one target and one drug hypothesis. However, most of the diseases are caused by a complex, multilevel combination of genomic, biological, and environmental factors. This contributes to a high degree of variability in disease development and responses to therapy. Traditionally, while diagnosing and treating, patients have been classified according to their clinical characteristics (i.e., phenotypes, or symptoms). Further, historically, therapeutic advances have been based on identifying relationships between the chemical structures of small molecule “drugs” and their effects on the biology of the disease (described as structure activity relationships, SAR), and subjecting these drugs to further combinatorial chemistry and computation chemistry. However, since novel drugs with fewer side effects and improved efficacy are becoming harder to identify, newer more efficient approaches are needed.
We are currently witnessing the era of precision medicine, as the fields of genomics, transcriptomics, proteomics, metabolomics, and proteo-genomics are gaining ground. Taken as a whole, this “Omics” approach involves integration of patient data while designing treatment regimens that are optimized for the patient and have a higher likelihood of successfully treating or controlling a particular disease, compared to traditional methods.
This new paradigm is called by different names, including individualized medicine, or precision medicine, or personalized medicine. According to an article in The Medical Futurist, 5 January 2019, entitled “The Omics Universe and its future”, genomics, transcriptomics, proteomics, metabolomics, and proteo-genomics occupy a growing field of research in systems biology. Rather than consider individual cellular components individually, systems biology essentially examines the interrelationship between all processes operating at the molecular level and evaluating the resulting data into one comprehensive assessment of the patient’s disease state. Omics sees the biological system as a collection of proteins and nucleic acid polymers (DNA, RNA, mRNA, etc.) and this system interacts on a number of levels within our biological system. The rapid advancement in these technologies as well as informatics has led to rapid advancements in further discovering more novel technologies. A decade ago, few thought it was possible to develop a vaccine against various types of cancers. Work is being done now on synthetic peptides that are designed based on the patient’s tumor cell sequencing and can be administered using a suitable delivery system. Research in this area may provide us with a vaccine targeting tumor angiogenesis.
As stated in The Medical Futurist article (see above) “…as more and more analytical and diagnostic techniques are incorporated into medical practice, Omics technologies will support the transition to precision medicine by offering a holistic view of a patient’s condition.” However, further streamlining of these technologies and extracting more information, faster and with greater efficiency will require the implementation of artificial intelligence (AI). As systems biology data collection becomes increasingly more complex, AI will play an integral role in assisting data analysts, algorithm generating mathematicians, and biostatisticians in their quest for solutions to the complex data presented to them.
Scientists at CureScience™ already launched an initiative for Omics technologies and AI analysts to work together – and drive precision medicine and predictive health forward.
Written by: Siva Yadavalli, Ph.D. and Lawrence D. Jones, Ph.D.
Key words: Omics Technologies, Precision Medicine, Genomics, Proteomics, Metabolomics, Proteo-genomics