Artificial Intelligence and Machine Learning will have a profound effect in transforming healthcare and bridging the historical gap of information asymmetry between the healthcare ecosystem and people

1. Batch of One
Batch of One
Leo Barella
Chief Technology Officer - Takeda

5. Genome
Transcriptome
Proteome
Phenotype Environment
(Diet, Age,
Lifestyle, Drug,
Disease)
What
could
happen
What
might
happen
What
is
happening

6. AI has broad utility across a number of use case
LIFE SCIENCES
• Disease Understanding
• Drug Repurposing
• Drug Discovery
PAYORS
• Risk Stratification
• Patient Engagement
• Customer Service
CARE DELIVERY
• Care Management Plans
• Treatment Selection
• Remote Monitoring
CONSUMER
• Nutrition
• Care Management
• Wellness

7. Life Sciences
REDEFINING BIOLOGICAL
UNDERSTANDING OF
DISEASE
The integration of clinical data, millions of
chemical profiles, in-vivo assay and AI
drives target discovery, generating more
effective leads at scale
DISEASE UNDERSTANDING
Breaking down biochemical processes and
physiology to better map natural history of
health, disease and the diagnostic process
specifically analyzing the interaction with
the individual patient
DRUG REPURPOSING
Mapping relationships between known
drugs to novel indications by creatively
leveraging compound libraries
DRUG DISCOVERY
With an understanding of structural biology
creating new classes of drug categories and
interventions.
It is more important to know what sort of
person has a disease than to know what
sort of disease a person has.
Hippocrates (460 b.c. - 375 b.c.)

8. Payors
RETHINKING RISK STRATIFICATION &
POPULATION HEALTH
Payors are aiming to strike a balance
between broad population coverage and
meeting members expectations on how
they
interact with technology. Further AI
approaches can help facilitate value based
reimbursement strategies
RISK STRATIFICATION
Applied analytics to predict patient
outcomes and inform treatment
recommendations
PATIENT ENGAGAMENT
Machine learning to tailor member outreach
based on clinical, claims and contextual
data
CUSTOMER SERVICE
Virtual agents to help members navigate
their benefits quickly and efficiently

9. Care Delivery
Gaining 360º view of
patient need
Care delivery can be viewed as a complex
process with many interdependencies.
AI approaches can help streamline the
delivery of care and how clinical insights
are discovered
CARE MANAGEMENT PLAN
Optimizing care management and creating
guidelines to manage follow-ups, intakes ,
readmissions and more
TREATMENT SELECTION
Identifying methods to provide better
treatments, early switch rates and improve
adherence
REMOTE MONITORING
Medical or Consumer grade sensors and
clinical algorithms track high risk patients
beyond facility walls

10. CONSUMER
Novel interfaces and
visual experiences
Consumer facing applications of AI are
emerging across every major health
segment.
Advancements in natural language
processing
(NLP), sensors, voice recognition,
augmented
reality (AR), sentiment analysis, and more
are
raising the sophistication of digital
interaction
and reshaping the consumer experience
NUTRITION
Virtual agents, food image analysis and
personalized nutrition based on
microbiome
and other biological determinants
CARE MANAGEMENT
Enabling personalized medicine, based on
the
use of genomics and research models
NOVEL EXPERIENCES
Interactive technology and new engagement
models via robotics