Pharmaceutical Outsourcing Q3 2023 - 26

CLINICAL TRIALS
Undoubtedly, the expectations for precision medicine are high.
Many believe that in addition to improving individual patient
outcomes, precision medicine also holds promise to reduce overall
treatment costs by eliminating ineffective or unnecessary medical
care and by identifying high-risk patients who need early targeted
care. In fact, a Harvard Business Review analysis projected that the
elimination of unwarranted variations in medical care through
use of precision medicine could potentially reduce the cost of
patient management by at least 35%.11
But, shifting paradigms
to precision medicine will necessitate overcoming many hurdles,
from technology and data integration challenges, to racial bias
in genetic population data, to privacy, cost and accessibility
concerns, to policy change, oversight and adoption logistics.
Multi-omic Data and Predictive Analysis in
Precision Medicine
The high expectations for precision medicine were recently
underscored in a report published by the US White House's Office of
Science and Technology Policy. The report is a follow-on to President
Biden's 2022 Executive Order on Advancing National Biotechnology
and Biomanufacturing Innovation. Among the many " bold goals "
presented in the report are two directed toward precision medicine.12
* Collect Multi-Omic Data - " In 5 years, collect multi-omic
measures in large cohorts with participants from diverse
populations and identify which measures are most relevant
to the diagnosis and management of at least 50 diseases with
high incidence and impact. " 12
* Enable Personal Multi-Ome - " In 20 years, develop molecular
classifications for diagnosis, prevention, and treatment to
address leading causes of disease-related mortality in the U.S.
and make these actionable with development of the $1,000
multi-ome. " 12
The report's focus on multi-omics data highlights the fact that
making precision medicine a reality is not just a matter of adopting
advanced technologies, like genome sequencing and biomarker
screening, or performing deep assessment of clinical data, immune
response, medical history, environmental factors, or behavioral
traits. Instead, it's about making sense of all that diverse data as a
whole, not as individual parts. This means collating, analyzing, and
connecting genomic and clinical data across huge population data
sets, leveraging predictive tools like machine learning and artificial
intelligence to identify trends, and then tying those insights back to
the lab, where treatments are developed, and to individual patientcare
settings, where treatment decisions are personalized. This is an
incredibly challenging endeavor given the volume and variety of
both data and experts involved in these processes.
Christian Olsen is the Associate VP, Industry Principal of Biologics at
Dotmatics, a provider of R&D scientific software connecting science, data and
decision-making.
Pharmaceutical Outsourcing | 26 | July/August/September 2023
Pharmaceutical Outsourcing Q3 2023

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