APR January/February 2022 - 11

« INSIDER INSIGHT
Clinical trials. Using computer vision in clinical trials could help
assess efficacy of drugs and their impact on patients by tracking and
identifying the vast amounts of datasets collected during the clinical
trial process. Researchers spend inordinate amounts of time observing
how specific treatments are working. Computer vision apps, for
example could be used on smart phones to monitor trial participants,
comparing health conditions to past data.
Assessing biomedical data. Beyond clinical trial data, most biomedical
data is unstructured, residing in different systems and formats, such as
scientific publications, clinical records, and other systems. Computer
vision can help to analyze documents and images and identify
biologically relevant information and correlations between data.
Regulating AI in Biopharma
As computer vision and other forms of AI emerge as key tools in life
sciences, the regulatory environment for AI-driven pharmaceutical
methods and medical devices is evolving and it can be questionable
as to how forms of AI are regulated by the FDA. According to a Pew
report, " currently, the FDA regulates some AI-enabled healthcare
products and it is considering how to adapt its review process for
AI-enabled medical devices that have the ability to evolve rapidly in
response to new data. " The report goes on to explain that the FDA
reviews software based on its intended use and the level of risk to
patients. Since it's intended to treat, diagnose, cure or prevent disease,
the FDA currently classifies it as a medical device.
Since AI algorithms in general, must be continuously trained based
on new data and changing situations, new inspections guidelines are
evolving, which may require new FDA approval each time algorithms
are significantly modified. Yet, the key goal is to ensure that AIassisted
discovery, diagnostics and treatments are enabling safe and
effective outcomes.
Computer Vision in the Future
Despite its nascent status in life sciences today, computer vision
has the potential to improve outcomes outside of the traditional
lab or clinic. Consider its implications in treating patients in wars or
natural disasters. Hand-held MRI or X-ray machines, equipped with AI
algorithms, could help detect conditions on the spot so that patients
can receive more effective treatment based on highly accurate
diagnoses. This type of intelligent diagnosis could also enable better
triaging of patients who require urgent care.
Challenges to Adoption
While there are many opportunities for computer vision in life sciences,
and it's already in use today by leading pharma firms, the primary
barrier to adoption is currently cost. Computer vision integration
requires a transformative shift, as well as significant investment by
companies to build the tech infrastructure. Currently there is a lack
of affordable CPU power to address the growing need to process the
huge datasets required. As major tech players, such as Apple and Intel,
work to deliver affordable CPU power, more and more providers will
join the effort, driving down CPU costs. Cloud and AI innovation, as
well as advanced edge computing capabilities are here today, and will
proliferate the market as the costs barriers to entry are lowered.
As life sciences and medical professionals have seen all too clearly
over the past two years, innovation abounds in how cures are found,
patients are treated and infection spread is managed. Computer vision
is playing a vital role, so that overworked clinicians and life science
professionals can receive the support they need to deliver highly
accurate data-driven results and focus their efforts on delivering the
most optimum patient outcomes.
Author Biography
Carlos M. Meléndez is the COO and co-founder of
Wovenware, a Puerto Rico-based design-driven company
that delivers customized AI and other digital transformation
solutions that create measurable value for government and
private business customers across the U.S. www.wovenware.com
www.americanpharmaceuticalreview.com |
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APR January/February 2022

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