(soft music)
We're in an era of amazing medical breakthroughs.
Some people have referred to it as a golden era of medicine,
but the paradox of it is
that the clinical development process
still remains challenging.
It takes a very long time, it's very costly,
and it has enormous potential to be improved
through further efficiencies and speed.
Patients are waiting for these therapies,
and the sooner that we can get them to patients,
the sooner that those patients
can benefit from those therapies.
AI has an enormous potential to help streamline
and accelerate clinical development.
There are strategic decisions
that need to be made at the beginning of a trial,
around the study design, which countries, which sites,
all of those decisions can be optimized.
This undertaking to create an AI-based clinical trial
is one in which you have to simultaneously
solve multiple problems.
And working with BCG,
we were able to identify the key workstreams
that were critical.
You had to get the data right,
you had to build a modern data platform
that was machine learning optimized,
a data science team capable of building predictive models,
intelligent applications
that our teams could actually benefit from,
and if any of those did not work,
the entire thing does not work.
Responsible AI was critical
in how we thought about bringing AI to Syneos Health.
In many cases the way we think about it is
AI produces the first recommendation,
but it's always filtered
through the expertise and judgment of an expert human.
We've seen enormous early indications of progress
in terms of acceleration.
We have been able to ultimately make better decisions
at the strategy level,
and share with sponsors the rationale, the evidence,
the data behind our recommendations.
I don't think we would've made
anywhere close to that progress
without the expertise of BCGX.
It used to be the case,
where the vast majority of the time
that data scientists spent,
was on the preparation, cleaning, mastering of data,
so it could be useful for analysis.
Now it's the inverse.
We have created through our data platform,
our data hygiene efforts,
the ability for data scientists
to spend only 20% of their time
with the basic requirements around data,
and 80% of their time delivering value through analysis.
The potential for AI to dramatically help biotechs
realize the value of their asset more quickly,
with greater certainty
and greater ultimate commercial impact is massive.
This whole idea of accelerating and maximizing
the impact of life-enhancing therapies
really drives the teams at Syneos Health.