Precision medicine represents the future of healthcare, transitioning away from the traditional “one size fits all” approach. Instead, precision medicine tailors disease prevention and treatment to the molecular profiles and environmental factors of patients. This paradigm shift is driven by advancements in technology, a deepening understanding of molecular mechanisms and biomarkers of disease, and a demand for more personalized treatments. In return, precision medicine promises better therapeutic outcomes, fewer side effects, and greater patient satisfaction.
At its core, precision medicine aims to match patients with the most effective treatments based on their molecular profiles. This more nuanced approach relies on the integration of “omics” data—genomics, transcriptomics, proteomics, epigenomics, metabolomics, and microbiomics—with other patient health information. Advancements in bioinformatics and AI-based tools are accelerating this integration to enable the prediction of disease risk and responses to treatments.
In this rapidly evolving landscape, new waves of technological innovations are enabling advances in healthcare. Wasatch Biolabs (WBL) has emerged as a pioneering force, uniquely positioned at the intersection of novel research and impactful clinical applications. Specializing in proprietary DNA methylation sequencing technology, WBL is an active participant and contributor to this movement.
This article explores recent advancements in precision technologies with a particular emphasis on their implications for clinical practice and the precision health market to keep you up-to-date with trends in biotech and healthcare.
The Food and Drug Administration (FDA) has acknowledged a vital need for “more mechanistic understanding of health and disease, improved manufacturing capabilities, and additional tools.” Innovations and advancements in next-generation sequencing, molecular profiling technologies, and bioinformatics and artificial intelligence (AI)-based tools are responding to this call.
Since the completion of the Human Genome Project in 2003, the field of genomics has witnessed an unprecedented advancement and democratization of sequencing technologies. Lower costs and higher throughput have made sequencing widely available to researchers and clinical service providers and have enabled innovations that drive precision medicine.
Long-read third-generation sequencing (TGS) technologies such as Pacific Biosciences (PacBio) and Oxford Nanopore Technologies have recently joined the scene, offering clinically viable solutions with several advantages over short-read technologies for certain applications. TGS advantages include long reads, native sequencing, and real-time analysis. This allows for native epigenetic analysis and greater resolution of difficult-to-sequence regions of the genome, such as copy number variations, repetitive regions, complex structural variants, and highly homologous regions.
Studies exploring the potential for TGS in resolving difficult-to-sequence regions demonstrate the clinical potential of the technology. For example, a recent study that used Nanopore sequencing accurately characterized 37 short tandem repeat (STR) loci associated with hereditary neurological and neuromuscular disorders such as Huntington’s disease, Fragile X syndrome, hereditary cerebellar ataxias, and others in a single assay1. These improvements in NGS technologies are expediting the clinical use of genomics-based tests.
Advances in omics technologies more broadly have revolutionized our ability to analyze the molecular profiles of individual cells with unprecedented detail2, moving beyond traditional bulk analyses that often overlook insights from rare cells and infrequently expressed transcripts and metabolites. Additional layers of data can now be added to single-cell RNA sequencing to elucidate chromatin accessibility, cell surface protein expression, and spatial behavior in addition to transcriptomics3,4.
Projects like the NIH’s BRAIN Initiative and the Kidney Precision Medicine Project leverage these technologies to map the cellular composition of organs, uncovering new details about health and disease at a cellular level. These efforts, part of a broader push to create comprehensive cellular atlases, are setting the stage for breakthroughs in how we diagnose, monitor, and treat diseases by illuminating the details of cellular function and interaction.
The integration of omics data in clinical practice, powered by bioinformatics, machine learning (ML), and artificial intelligence (AI), is transforming healthcare, offering deep insights into the molecular underpinnings of health and disease.
Bioinformatics combines biology, computer science, and statistics to manage and interpret biological data. Developing tools capable of DNA base calling and decoding complex genetic information reveals key insights into genetic variations and molecular pathways. The analytical power of bioinformatics supports the customization of patient care based on genetic profiles.
ML and AI enhance this data-rich landscape by identifying patterns within omics data that traditional methods might miss, enabling more robust drug discovery and the prediction of disease risk, treatment responses, and patient outcomes. AI, in particular, can apply these findings in real-world settings, automating diagnostic and treatment processes to facilitate drug discovery and the personalization of treatment plans. Together, these technologies harness the power of omics data and electronic health records to create patient-specific treatment strategies, marking a significant leap toward the realization of precision medicine.
The Cancer Genome Atlas (TCGA) has been a pivotal project in utilizing bioinformatics to explore the genetic makeup of various cancers. By cataloging genetic mutations across thousands of tumors, TCGA has created a vast repository of data that serves as a foundational resource for both research and clinical applications. As a publicly available database, the bioinformatics achievement now feeds into ML, where researchers can analyze the data and develop clinically relevant tools like polygenic risk scores (PRS). These scores assess the cumulative risk of developing cancer based on the presence of multiple genetic variants. AI can leverage insights from ML to further personalize cancer care.
The widespread integration of multi-omics technologies into clinical practice is still in early stages but is rapidly progressing, with several areas of notable advancements:
Precision oncology is one of the largest and most advanced applications of precision medicine. Oncology remains at the forefront of integrating genetic and molecular information into patient care, largely due to the inherently genetic nature of cancer development and progression. Precision oncology tailors cancer treatment to the genetic mutations and unique characteristics of an individual’s tumor for effective patient outcomes.
The National Cancer Institute’s (NCI) Molecular Analysis for Therapy Choice (MATCH) trial is a testament to this transformative shift in cancer treatment. This groundbreaking trial took a tumor-agnostic approach to cancer treatment by investigating the potential of grouping and treating tumors by their molecular biomarkers instead of tumor types. Concluding in 2023, it engaged 1,201 participants across 38 distinct study arms, marking it as one of the most extensive and thorough precision oncology trials to date. The study found that genomic sequencing could significantly benefit individuals with advanced cancers by informing their personalized treatment strategies. Building upon the pivotal outcomes of the MATCH trial, a suite of follow-up studies—ComboMATCH, MyeloMATCH, and ImmunoMATCH—are now in progress. These subsequent trials aim to deepen our understanding and application of precision oncology by exploring combinations of therapies, improving clinical trial recruitment with new screening methods, and identifying biomarkers that predict the efficacy of immunotherapy treatments, respectively. These approaches have fueled a movement toward defining disease by molecular signatures rather than clinical symptoms.
Molecular diagnostics are revolutionizing the diagnosis and treatment of disease by leveraging molecular markers such as genes, mutations, and gene products. Liquid biopsies, a key advancement, analyze biomolecules from body fluids such as blood, urine, and saliva. As such, they are a less-invasive and generally more cost-effective alternative to traditional tissue biopsies. Reducing invasiveness enhances the potential for repeatability, offering a more dynamic view of a disease’s molecular profile and how it changes over time, which is essential to guide personalized treatment.Liquid biopsies have been particularly impactful in oncology, enabling the identification of mutations like EGFR in small-cell lung cancers to guide targeted treatments5.
Liquid biopsies are also expanding to other therapeutic areas, such as cardiovascular diseases, neurological conditions, and pathogen infections. These broadening applications demonstrate the potential for liquid biopsy to transform diagnostics and disease monitoring across a wide range of conditions, facilitating the accessibility of precision medicine.
Pharmacogenomics, which aims to customize medication types and dosages based on patients' genetic profiles, is also a rapidly evolving field. This approach focuses on genetic factors that affect drug metabolism, efficacy, and toxicity. Pharmacogenomics is particularly relevant in psychiatry, where selecting the right medication has traditionally been a trial-and-error process. Genetic tests, including those analyzing CYP enzymes, enzymes involved in the metabolism of drugs, are playing a central role6.
While the integration of pharmacogenomics in clinical psychiatric care is progressing, its application faces challenges. These include the need for stronger clinical evidence, improved cost-effectiveness, and established guidelines. Despite these hurdles, the capacity of pharmacogenomic tests to predict individual drug responses—potentially avoiding ineffective treatments and minimizing side effects—marks a noteworthy advancement toward personalized psychiatry. Pharmacogenomics continues to develop as an essential component of precision medicine, promising to refine and personalize treatment strategies for psychiatric disorders, cancers, cardiovascular diseases, and other conditions to enhance patient care and treatment outcomes.
Predictive analytics leverage the power of bioinformatics, statistical models, and machine learning algorithms to analyze medical data and predict medical outcomes such as disease risk, prognosis, and response to treatment. The approach utilizes a wide range of data, including omic data, medical history, and other patient data such as lifestyle factors to make informed predictions about patient health.
For example, the development of risk models for type 2 diabetes showcases predictive analytics in action. Using large health datasets and machine learning algorithms that sift through genetic markers and lifestyle factors, these models can assess an individual's risk of developing diabetes7. The advanced prediction would enable healthcare providers to intervene earlier than they might with traditional tools, offering personalized lifestyle and treatment plans tailored to the patient’s specific risk factors. Such targeted interventions are projected to significantly prevent or delay the onset of diabetes, demonstrating the transformative potential of predictive analytics in enhancing patient care and outcomes.
Rare disease testing employs molecular diagnostic techniques to detect and diagnose rare disorders. Over 7,000 rare diseases have been identified to date. Estimates suggest that as many as 80% of these rare diseases have a genetic basis8, yet it takes an average of 4-5 years to receive an accurate diagnosis. Whole genome sequencing (WGS) has increasingly been suggested for rare disease testing for its comprehensive ability to detect single nucleotide variants (SNVs), structural variants (SVs), and other types of variants such as repeat expansions9. With the decreasing costs associated with whole genome sequencing (WGS), the prospect of widespread adoption for rare disease testing is increasingly feasible, with the potential to dramatically shorten the diagnostic journey for patients with rare conditions.
According to Research and Markets, the Precision Medicine Market is projected to experience robust growth from 2023 to 2033 and was estimated to surpass $78.1 billion in 2023 global revenue. Though oncology remains the largest clinical application of precision medicine and is projected to grow due to the increasing global burden of cancer, the growing precision medicine market is also driven by the broadening applications of precision medicine to therapeutic areas beyond cancer, including neurological and psychiatric disorders, immunology, respiratory conditions, and genetic and rare diseases. The market is also driven by the increasing demand for targeted therapies and the growing precedent of precision medicine over traditional “one size fits all” approaches to healthcare.
As rapid advancements in molecular profiling technologies and the development of sophisticated predictive algorithms fuel this fundamental shift in healthcare, the potential for precision medicine is becoming increasingly clear. But this is just the beginning. The field of precision medicine is rapidly progressing, so staying informed is key.
Wasatch Biolabs (WBL) is not merely an observer of this revolution. WBL is an active contributor, dedicated to redefining clinical services and molecular diagnostics. Our proprietary technologies and innovative approach to DNA sequencing reflect our commitment to expediting precision medicine and its benefits for patients through targeted, data-driven solutions.
Whether you are a researcher seeking new insights and innovations, a clinical service provider aiming to improve patient care, or simply someone interested in precision medicine, you can be a part of the conversation. Visit www.wasatchbiolabs.com to stay informed of the latest trends, research insights, and breakthroughs in biotech and precision health.
