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Global Translational Medicine Personalized, multi-omics disease detection

7.4. Longitudinal and personal multi-omics This envisioned future in health-care represents a
characterization profound shift from the reactive model of treating diseases to
Once collected, these biosamples are transported to a central a proactive, preventative and highly personalized approach
laboratory and subjected to comprehensive multi-omics to maintaining health and managing illnesses. It enables early
characterization. State-of-the-art mass spectrometry and detection of health deviations, rapid intervention and precise
other suitable sequencers are employed to analyze the genetic, treatment strategies. Ultimately, this convergence of wearable
transcriptomic, proteomic, metabolomic and other omics technology and multi-omics characterization empowers
profiles, as well as the targeting of specific immune markers individuals, researchers, and health-care professionals
in the samples. A suite of automatic bioinformatic analyses alike to unlock the full potential of personalized medicine,
is triggered as soon as the data is generated. Albeit shallow, advancing the goal of optimal health and wellbeing for
this detailed multi-omics data provides a rich understanding all. Global implementation might be unattainable in our
of the molecular underpinnings of the health deviation and lifetimes, but this new, unified approach can be first attempted
provides a personal fingerprint of molecular data. in clinical trials conducted by the medical industry, where
many of the mentioned techniques are already enlisted in
7.5. Guiding physician decision making one shape or form. Identify relevant patient groups is another
The insights gleaned from multi-omics characterization factor that needs to be considered. Patient populations with
serve as a powerful tool for healthcare providers. Armed certain chronic diseases and with a clear and vital treatment
with this data, physicians can make informed decisions intervention might be a first target subject group for testing
regarding the most appropriate course of action. This the feasibility of the proposed approach.
may involve closer monitoring, additional in-clinic In the ever-evolving healthcare landscape, personalized
analyses, tailored therapeutic interventions, or, in cases multi-omics characterization emerges as the future of
where the deviation is a transient anomaly, reassurance medicine. Integrating multiple omics technologies provides
for the patient. Importantly, the turnaround time from a holistic understanding of individuals, enabling precise,
the triggering of the automatic alarms system from the and data-driven health-care decisions. This explosion of
wearable technology to the generation of an analyzed, omics research further exemplifies how collaborative efforts
personal multi-omics profile should only be a few days continue to drive innovations in translational research and
for the doctor’s convenience. This approach facilitates expand our understanding of complex diseases. As wearable
preemptive identification of adverse side effects, enabling technology merges with multi-omics analysis, we are on the
early detection, possibly even in advance of symptomatic cusp of a new era, where proactive, personalized healthcare
manifestation in the patient. becomes the norm – where we could detect untold ailments
days before the patient is even aware of their predicament.
8. Concluding remarks The transformation we see currently in medicine marks
Wearable devices have the potential to significantly benefit the dawn of a truly personalized era and, if implemented
clinical trials by detecting side effects, correcting dosages, correctly, we could detect disease before we know it.
improving understanding of the mechanism of action,
identifying drug-drug interactions and complementing Acknowledgments
other data-driven interventions. Moreover, if implemented I would like to thank Alberto Santos Delgado and Fabrice
correctly, this approach could reveal drug efficacy. With a Chimienti for their valuable contributions to this review.
likely future’s increases in sensitivity and depth, it could Their expertise in omics-bioinformatics and wearables,
even be applied to healthy subjects in a phase 1 clinical respectively, and their insightful feedback helped shape
trial, where downstream pharmacodynamic effects may the analyses. Furthermore, I would like to thank Edward
be evident from a multi-omics data set, depending on the Handyside for his valuable input and expertise in
drug and dosage being studied. editing this manuscript. His assistance was very helpful
However, it is important to consider the additional costs in improving the clarity and readability of this paper.
associated with implementing this system. Comparing I am grateful for all my colleagues support, and positive
the cost increase to that of a failed clinical trial phase attitude throughout the process. Finally, I would like to
can help evaluate the feasibility of this approach. Despite acknowledge the application ChatGPT in improving the
the potential costs, incorporating wearable devices into clarity and coherence of my work.
clinical trials can lead to more accurate drug development
and improved patient outcomes, and ultimately retained Funding
value of investments. None.

Volume 3 Issue 1 (2024) 9 https://doi.org/10.36922/gtm.2357