Genes have long been studied to understand their role in inheritance – this field is known as genetics – but genomics takes things a step further.
Although direct-to-consumer genotyping services like 23andMe are sometimes in conflict with the FDA for making health claims in their reports, genomics has made significant strides toward clinical utility.
Mass Affordability of Sequencing
Genomic sequencing costs have decreased so significantly that for some patients, clinical genomics testing now makes sense as an insurance benefit.
But many health systems remain unprepared to make the shift, which requires new forms of genetic testing as well as integration of genomics into care pathways and evidence-based medicine protocols. Payers will play a vital role in helping health systems adapt successfully.
Few innovative companies are rising to this challenge. PacBio stands out among them by using long-read sequencing technology that offers higher fidelity genome and transcriptome data than competing systems – helping scientists unravel complex biological systems influencing health, disease, and treatment. Their technology can find genetic variations as small as part-per-million level genetic variation and herald a new era of multiomics research.
PacBio innovations are helping scientists uncover all of the genetic, epigenetic, and metabolomic information encoded within one cell – revolutionizing our ability to understand how these factors interact. These discoveries may inform future drug discovery efforts more accurately by providing greater insight into whether potential candidates work in particular tissues or organisms or interact with other chemicals or medicines.
PacBio technology has revolutionized cancer screening. PacBio has already transformed how genetic mutations found in leukemia cells can be identified and matched to appropriate therapies, while also increasing chances of enrolling in clinical trials that fit a patient’s diagnosis.
Gene therapy, once considered the granddaddy of genomics, is experiencing a revitalization thanks to CRISPR/Cas9 genetic scissors developed by Emmanuelle Charpentier and Jennifer Doudna. They enable scientists to make precise changes to genetic material within cells with unparalleled accuracy – turning on or off functions with greater precision than ever before.
As genomics for all becomes mainstream, more health systems will need to move away from high-margin services like chemotherapy infusion suites and operating rooms and toward high-impact applications like genomics tools that will assist physicians and patients alike in making use of this transformative technology.
Decentralization of Clinical Sequencing Applications
As sequencing costs decline, more researchers will have access to genome data and apply it in clinical trials, leading to more targeted therapies that better address genetic mutations that cause disease, as well as more accurate diagnoses of patients’ conditions.
Genomics marks a dramatic departure from traditional medicine practices that focus on treating individual symptoms and risk factors for treatment purposes. Genomics seeks to identify specific mutations within cancer cells which drive its development, then develop drugs to specifically target these mutations.
Genomics is an umbrella term encompassing the study of an organism’s DNA — both its genes encoding proteins and non-coding regions. Genomics seeks to understand how those genes interact with each other to influence an organism’s behavior and function, as well as examine any correlations between genotype and phenotype (the way an individual looks and behaves).
Over the past decade, genomics has seen tremendous advances thanks to technological innovations in sequencing hardware. Early methods involving capillary sequencers such as ABI’s PRISM 3100 were costly and time consuming; today whole genomes can be sequenced within hours using high-throughput DNA platforms like Illumina’s HiSeq 2000.
Genome sequencing is an essential step toward understanding the molecular biology of humans, plants and animals alike. But its data output can be overwhelming; therefore requiring sophisticated computational tools to manage and interpret.
Genomics annotation, or attaching biological information to genomes, is an integral component of genomics. This can be accomplished manually using tools like BLAST or automatically through genome-agnostic algorithms that search for similarities across genomes. Some databases offer integrated tools that use similarity searches along with genome context information and experimental data from other sources to automate genome annotation processes.
Decentralized clinical trials represent another advancement in genomics. Participants can participate remotely by using digital technology and home sample collection kits, increasing participation from populations that would otherwise be excluded due to distance or mobility restrictions. They also produce real-world genomic and phenotypic evidence in participants’ natural environments that is more indicative of how investigational products will perform over time.
2025: The Year of Multiomics
Multiomics promises to revolutionize medicine as it provides a comprehensive view of biological systems. By integrating data from other omics layers such as transcriptomics (all the RNA transcribed from DNA), proteomics (protein structure and function), and metabolomics (biochemical changes), scientists can uncover deeper and more complex insights, leading to personalized medicine–shifting healthcare from being one size-fits-all towards anticipatory care that uses molecular profiles to detect disease risk years before symptoms appear, providing physicians with more targeted treatments for each individual patient.
Genomics offers a static snapshot of an individual’s genetic code; multi-omics gives a dynamic portrait. Just as blueprints reveal only foundational structures of buildings, multi-omics reveals living narratives of these houses by detailing how each room is used and what its contents are (transcriptomics), events happening inside it (proteomics), and measuring consumption rates of supplies consumed (metabolomics).
Biological systems are inherently complex, making the capture and analysis of large datasets an ongoing challenge for many researchers despite advances in sequencing technology. Real-world clinical data as well as open access platforms are helping researchers overcome barriers to multiomics analysis.
There is still room for improvement when it comes to data harmonization. Genomic and metabolomics data may be stored in disparate formats, making combining them an extremely challenging task. Relying on advanced computational methods based on neural networks or machine learning could facilitate the process of unifying disparate datasets more efficiently.
The next wave of genome sequencing will not only advance genomics and multi-omics, but will also foster spatial genomics – an approach to studying biological molecules within their native tissues – allowing researchers to better understand biological molecules within their natural environments. Spatial genomics promises to become an invaluable tool in cancer detection by immunotherapy or personalized treatments; additionally it may allow better understanding between pathogens and host immune responses as well as more effective vaccine design.
2025: The Year of AI-Powered Analytics
As AI-powered analytics becomes more prevalent, demand will also increase for data analysts with strong analytical and communication skills who are capable of taking full advantage of it. Data analysis tools that empower users to quickly comprehend AI models will become essential.
AI technology has already become a global trend. Companies worldwide are turning to artificial intelligence (AI) to accelerate data analysis, reduce time-to-insight, and free data teams up for strategic focus. Retail and CPG organizations, for example, are adopting AI into everyday processes in order to automate workflows, surface predictive insights and enhance customer experiences.
These tools are also improving the quality and usability of data visualizations, including error detection and warning users of miscalculations during data creation, making data sets more accurate and trustworthy. Furthermore, some are helping users build models with more intuitive interfaces so they may gain a deeper understanding of model outputs.
AI technology enables users to analyze large data sets more quickly by eliminating entry barriers for more people. For example, AnswerRocket allows anyone to connect data from various sources and ask simple English-based questions in order to gain proactive insights and recommendations based on underlying information. This represents a vast improvement over traditional data analyst work practices whereby they must rely on spreadsheets and APIs with complex structures for answers they require.
As more data professionals gain access to the appropriate tools, businesses will be better-equipped to make more informed decisions, prompting further adoption and deployment of AI-powered analytics. However, this also highlights the need for effective governance policies to be put in place and enforced so as to protect users safely.
Organizations need the right technology to quickly deploy, scale, and manage intelligent analytics quickly and easily. MicroStrategy ONE offers organizations an efficient AI-powered analytics process with powerful workflows, unlimited data access, cloud native architecture and unbeatable performance – helping businesses transform their analytics process with AI powered analytics for unrivalled performance.
