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prashanth updated resume 2024 for Teaching Profession
Gloflow Engr245 2021 Lessons Learned
1.
2. GloFlow
Lessons Learned
From Slide Digitization technology To Response Prediction For Cancer Treatment
126 interviews
Anirudh Joshi
Hustler
Damir Vrabac
Picker
Viswesh Krishna
Hacker
Pranav Rajpurkar
Designer
Nicky Kamra
Mentor
3. Our background
Anirudh Joshi
M.S. Computer Science
Built technologies @
Damir Vrabac
M.S. Electrical Engineering
Startup Founder +
AI in Industry
Viswesh Krishna
B.S. Computer Science
Pranav Rajpurkar
Ph.D. Computer Science
Startup founder on phone-
based eye care screening
36 publications (8500+
citations) in AI + Medicine
Instructed Coursera AI for
medicine to 40k+ students
4. For pathology labs who have
difficult cases who find mailing
physical slides for secondary
consults too slow and
expensive. GloFlow was a
platform that enables digital
secondary consults with
expert pathologists.
Week 1-2: External Consultations
make Digital Pathology useful.
HIPAA compliant
cloud storage
Pathology Lab Academic
Center
1. Pathology labs were very interested and wanted to use this platform.
2. Academic Center had no immediate incentive to move digital.
3. Two sided marketplace not possible with only one endpoint.
💡
5. Week 3: Pivot to AI tools for Pathology labs.
Lessons 💡
1. Pre-clinical studies have few
barriers to entry
2. AI can speed up existing
workflows and identify new
features
3. Current tools satisfy needs
Rare Event
Detection
What task would you like to perform?
Tissue
Quantification
Cell
Segmentation
Tissue
Segmentation
Went back to the drawing board -> Pivot
For pathology labs who need to provide
insights to customers, GloFlow is a suite of
AI tools for preclinical tasks that enables
accurate scalable insights without needing
an in house AI team and identifies new
features not detected by current AI tools.
6. Week 4: Pivot to AI Pathology tools for Genomics
companies.
Lessons 💡
1. Quality Control in Genomic
workflows could use AI tools to
scale up
2. Mistakes in Quality Control can
seriously impact downstream
sequencing tasks
3. It was cost-effective to simply
sequence everything
On your selected patch:
Tumor purity = 60%
Epithelial cell count = 5
Region of interest on whole
slide image fraction:
25%
Inflammation score
6 of 10
For heads of product and R&D for
genomic companies who need to
automate high volume pathology tasks,
GloFlow is a platform
that uses AI to scale pathology tasks.
7. Week 5-6: Virtual Genomic Sequencing from slides
could identify drug targets.
HCC
CRC
NSCLC
SAMPLE_1
SAMPLE_2
SAMPLE_3
CTNNB1 FMN2 TP53
Key Mutation Prediction Molecular Pathway Prediction
Lessons 💡
1. Virtual Genomic Sequencing was was
a vitamin (not a painkiller)!
2. To motivate pharma to share data
and initiate pilots, we needed to
complete the value chain and make
the value prop more significant.
Mutation Prediction helps identify drug
targets for pharma companies.
Research points to there being a signal in
slides for spatial expression prediction.
The slides will be available for diagnosis for
years to come.
8. Biomarker discovery & patient selection with Pharma
- “If this tool could be applied to ovarian tumor and identify subtypes of patients
that didn’t respond that could be a path of proposing a combination of
checkpoint inhibitor therapy”
- - Head of Computational Biology Oncology R&D, Pfizer
Is Cost a Value Prop:
- “Given clinical trials are millions of dollars, pharma is not going to skip out on
cost for the patients. Technologies are likely more valuable for other
purposes.” - Professor of BMDS at Stanford
Week 7: Predicting response to treatment instead
of virtual molecular test may be more useful!
9. MVP: Multimodal Patient Data to Response
Prediction with Analysis
Upload
Patient Data
H&E Slide
Genomics
Likelihood of
patient
responding to
drug
Explaining why
the patient may
not respond to
the drug
10. Biomarker discovery & patient selection with Pharma
- “Focus on having the largest effect size, not the number of patients with a
disease. Unless you’re a Pfizer or Merck, it doesn’t matter if you have a
relatively smaller patient population” - CEO of AI biotech
What the technology needs to show?
- “Show me a marker of resistance, and show me a marker of sensitivity (will
respond to chemo but not another treatment type)” - medical oncologist
studying genomics of cancer, UCSF
Week 8: Be careful what cancer you choose, but clear
value if you are able to make these predictions
11. Week 1-2: Digital Pathology
Consult Platform
Week 3: Pre-
clinical AI tools
Week 4: Quality
Control for Genomics
Week 5-6: Virtual
Genomic Sequencing
Week 7-8: Response
Prediction for Oncology
12. What’s Next
Summer
Data Partner
Partner to build
data / tech
Non-binding
agreements for
Pharma
Fall
Seed Round
Results from first
pilot
First Pharma
contract
Incorporation
June 14th
14. Every piece of our business model canvas changed
Pathology labs at
hospitals and private
practices who need
assistance on
difficult cases.
Academic centers
who want to reduce
administrative cost
associated with
consults.
Integration with
current medical
record systems
Academic pathology
labs on the platform
Validated AI models
for diagnosis
assistance
Problem:
Secondary
consultations in
pathology involve
physically mailing
slides which takes a
long time due to
administrative and
logistical overhead
Needs:
Platform for on
demand secondary
expert consults.
Access to AI
assistance for
diagnosis
Hospital Pathology
Labs
Pathology
Reference Labs
Academic Hospitals
AI Pathology
Companies
Whole Slide
Scanning
Companies
Salaries for employees
Cloud compute for software platform and AI inference
Regulatory validation trials
Marketing for conference sponsorship
Percentage of the secondary consultation fee for
facilitating the consult (similar to marketplace
model).
Subscription fee for using AI assistance
Medical Conferences
Website
Professional
Associations
Expert pathologists
at academic centers
Software platform
Annotated data for
AI
As a B2B company,
our customers
expect an
enterprise product
with emphasis on
reliability, support
and privacy.
Predict key mutations
directly from H&E
slides for for either
sequencing,
retrospective analysis
and developing
targeted therapeutics
Direct: Pharma &
Genomic companies
Heads of Oncology
at Pharma
Companies
Pharma contracts
Compute
Annotated Data
Integrate into
pathology workflows
at pharma co.
Train AI solutions
Head of Oncology at
Pharma
Providing our
customers with
higher quality
outputs with
increased usage
CDx reimbursement
Head of Biomarker
Discovery at Pharma
Companies
Head of Biomarker
Discovery at Pharma
company
Grow portfolio of
cancers targeted
Response prediction of
patients based on
multimodal data (H&E +
genomics)
AACR, SITC
Drug specific
models for response
prediction
Salaries for
employees
Cloud Compute
Dataset purchases
15. We came in with a research lens, and are
walking out with a broader lean launchpad lens
“Be bold in your vision, the future looks very different from today.
Be the one to rethink it.”
“Iterate! You don’t need to build a product to validate the market.
Ask questions, present clear MVPs, and make quick iterations
before building.”
Thank you to the teaching staff, and especially to our
mentors Steve Blank and Nicky Kamra, for extremely
valuable steering each week.
Gained new
insights
every week