The document discusses how AI is expected to transform the patient journey in healthcare, with a focus on digital health, big data analysis, and personalized medicine. It outlines a future scenario for lung cancer patients in 2024, detailing advancements in screening, diagnosis, treatment, and prevention enhanced by AI technologies. Moreover, it emphasizes the importance of data sharing, patient participation, and a collaborative approach among various stakeholders in the healthcare ecosystem.

1. How will AI affect the patient journey of the future?
Dr.-Ing. Matthieu-P. Schapranow
Clinical Trials Europe Conf., Basel, Switzerland
Oct 16, 2019

2. ■ 1998: Founded as public-private partnership in Potsdam, Germany
■ 15+ professors, 600+ B.Sc. & M.Sc. students, 170+ PhD students
■ Since 2017 Digital Engineering Faculty of Potsdam University
■ Digital Health Center: Connected Health, Digital Health & Machine Learning,
Personalized Medicine, In-Memory Computing for Digital Health
Hasso Plattner Institute
Key Facts
How will AI affect the
patient journey of the
future?
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Schapranow, Clinical
Trials Europe Conference,
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3. ■ Long-lasting digital health expertise and access
to global network of subject-matter experts
■ Database: In-memory database technology
for real-time data analysis
■ Methods: Latest artificial intelligence
and machine learning algorithms optimized
for scalable high-throughput processing
■ High-throughput processing of *omics data and
big medical data modalities
Working Group In-Memory Computing for Digital Health
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Trials Europe Conference,
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4. Newborn pics
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Trials Europe Conference,
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PhotobyJensJohnsson

5. How will AI affect the
patient journey of the
future?
Newborn pics
Schapranow, Clinical
Trials Europe Conference,
Oct 16, 2019
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Personal Risk Score
Chord Blood /
Stem Cells
DNA Repair
CRISPR/Cas 9
Bred or Donated
Organ
Glucose Sensor
Nutrition Sensor
Heart Monitoring /
Implanted Defy
Hearing Aid
PhotobyJensJohnsson

6. ■ Case vignette: 65-year old, male, former smoker, COPD patient
■ How his patient journey looks like?
Patient Journey: Lung Cancer in 2024
Screening, Diagnosis, Treatment, and Prevention
Schapranow, Clinical
Trials Europe Conference,
Oct 16, 2019
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patient journey of the
future?
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7. Schapranow, Clinical
Trials Europe Conference,
Oct 16, 2019
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patient journey of the
future?
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8. Our Approach: AnalyzeGenomes.com
In-Memory Computing Platform for Big Medical Data
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Trials Europe Conference,
Oct 16, 2019
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patient journey of the
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In-Memory Computing Platform
Extensions for Life Sciences
Data Exchange,
App Store
Access Control,
Data Protection
Fair Use
Statistical
Tools
Real-time
Analysis
App-spanning
User Profiles
Combined and Linked Data
Genome
Data
Cellular
Pathways
Genome
Metadata
Research
Publications
Pipeline and
Analysis Models
Drugs and
Interactions
Drug Response
Analysis
Pathway Topology
Analysis
Medical
Knowledge CockpitOncolyzer
Clinical Trial
Recruitment
Cohort
Analysis
...
Indexed
Sources

9. ■ Personal risk score based on patient anamnesis, e.g. COPD or
former smoker, regularly calculated by algorithms
■ à Regular check-ups supported through direct notifications, e.g.
annual respiratory screening recommended
Patient Journey: Lung Cancer in 2024
Screening
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Trials Europe Conference,
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10. ■ 150 MEUR national initiative to support adaption of digital health
■ HiGHmed consists of international partners from, e.g. hospitals,
academia, and industry.
■ Clinical Use Cases
□ Oncology
□ Cardiology
□ Infection control
■ Education: Curriculum for experts, e.g. data scientists, data stewards
Our Cooperation Partners:
HiGHmed Consortium
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11. ■ Lung function test + low-dose CT scan of the lung
■ AI system supports radiologists in detecting lung tissue changes
■ Minimal invasive CTC test reveals cells carrying relevant genetic
changes, e.g. EGFR+ and ERBB2+
■ à Biopsy from lung validated hypothesis
Patient Journey: Lung Cancer in 2024
Diagnosis
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Trials Europe Conference,
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https://www.plattform-lernende-systeme.de/anwendungsszenario-2.html

12. Use Case: Precision Oncology
Identification of Best Treatment Option for Cancer Patient
■ Diagnosis: Non-Small Cell Lung Cancer (NSCLC), stage IV
■ Markers: EGFR, ERBB2
1. Send tumor sample to laboratory for DNA extraction
2. Sequencing of tumor DNA is possible in <24hrs
3. Analysis involves 1+ TB of raw genome data per sample and takes days
4. Process raw genome data, e.g. alignment, variant calling, and annotate
5. Identify relevant variants using international medical knowledge
6. Decision making requires global medical knowledge, e.g. similar cases
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13. ■ AI-based therapy support based on, e.g.
□ Clinical guidelines
□ Historic patient cases
□ Latest international medical
knowledge and publications
■ à Fully compliant with latest clinical
guidelines surgery can be performed
Patient Journey: Lung Cancer in 2024
Treatment
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Trials Europe Conference,
Oct 16, 2019
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https://we.analyzegenomes.com/mkc/digiGipfel2018/

14. Use Case: Molecular Tumor Boards
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■ Multidisciplinary exchange format
for oncologists
■ Incorporates genetic dispositions
■ Focus on data management, e.g.
data retrieval, variant annotations,
case presentations, documentation,
and follow-up

15. ■ Comparison of outcome of similar patients
■ Quantitative real-time analysis of therapy efficiency
■ Assessment of alternative therapy options
■ Break-through: bringing clinical trials to participants
■ à Adjuvant therapy based on specific
combination of chemotherapy is selected
Patient Journey: Lung Cancer in 2024
Treatment
Schapranow, Clinical
Trials Europe Conference,
Oct 16, 2019
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patient journey of the
future?
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https://we.analyzegenomes.com/mkc/digiGipfel2018/

16. Use Case: Medical Process and Knowledge Support
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Trials Europe Conference,
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■ Identification of cluster of similar patients
■ Real-time analysis of clinical guidelines incorporating patient specifics

17. Use Case: Real-time Assessment of
Clinical Trial Candidates
■ Supports trial design and recruitment process through
statistical data analysis
■ Real-time matching and clustering of patients and
clinical trial inclusion/exclusion criteria
■ Reassessment of already screened or participating
citizens to reduce recruitment costs
How will AI affect the
patient journey of the
future?
Real-time assessment of
clinical trial candidates
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18. ■ Federal Institute of Digital Health Data envisioned:
□ Maintains population data for a healthier society
□ Provides access to subject-matter experts
□ Supports development of innovative DH solutions
■ Data Donation Pass as citizen-facing tool:
□ Enable sovereign use of healthcare data
□ Control access to personal healthcare data
□ Donate de-identified data for research projects
Patient Journey: Lung Cancer in 2024
Prevention
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Trials Europe Conference,
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https://we.analyzegenomes.com/apps/data-donation-pass/

19. Citizen Participation in Healthcare
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PhotobyBenDuchac
Citizen Participation is Key
■ Today, acquisition and processing of fine-grained healthcare data is no longer a limitation
■ Every individual is a valuable source of data, e.g. to better understand population health
■ Digital solutions are not for free, but they facilitate lean processes in healthcare
■ Healthy citizens can help to design innovative and helpful solutions

20. Stay in Contact
Dr.-Ing. Matthieu-P. Schapranow
Group Leader & Scientific Manager Digital Health Innovations
Hasso Plattner Institute
Digital Health Center
Rudolf-Breitscheid-Str. 187
14482 Potsdam, Germany
we.analyzegenomes.com
@AnalyzeGenomes
Schapranow, Clinical
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Oct 16, 2019
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