PDT 78 - $6.5M - Seed - Pepper Bio.pdf

2. Patients need to be lucky in order to be treated effectively
2
Check-up
Lung Cancer
• Tissue specific
• Mutation specific
Diagnosis
Poor
outcome
Treat
Poor
outcome
Respond
Poor
outcome
Healthy
No treatment
available
No response to
treatment
Disease develops
resistance
Small percentage
of patients

3. I have been there, when my grandmother got Alzheimer’s,
where there are no treatments
3
Check-up
Alzheimer’s
• Behavioral
• Imaging
Diagnosis
Poor
outcome
Treat Respond Healthy
No treatment
available

4. CSO & Co-founder
PhD, MIT
SAMANTHA
DALE
STRASSER,
PHD
Pepper team has the scientific rigor and business acumen for success
JON HU
CEO & Co-founder
MBA, Harvard
Business School
• Led Atidiv (formerly Loft), an enterprise solutions
Guild portfolio company, as its CEO, growing the
company from 200 to 300 people
• Expanded Techweek, a tech conference and Guild
portfolio company, to 2 new cities as COO
• Developed Pepper’s technology
• Studied multi-omics while an NSF Graduate
Research Fellow in EECS mentored by Douglas
Lauffenburger at MIT
• Former Churchill Scholar and Goldwater Scholar
SIMON FRICKER,
PHD
CDO
PhD, University of
Warwick
• 25+ years of experience in the industry from a
founding member of AnorMED (acquired by Genzyme)
to Sanofi
• Worked on 3 approved drugs, including overseeing a
drug from beginning to approval
4

5. Industry
researchers
identified 3
fundamental
problems with
drug discovery
5
Studies lack functional information
and focus on ‘what is there’
not ‘what is happening’
Static
Correlative
Analyses miss causative
interactions and depth
Researchers often look in the
wrong places when using
limited panels
Biased

6. Pepper’s transomics approach ushers in a new era of drug discovery
6
Phosphoproteomics
Modified protein data
provides a functional
understanding of biology
Proteomics
Transcriptomics
Genomics
Traditional R&D
Static
Limited
Unlinked
Global data across all
layers captures full
complexity of biology
Incorporating universal
interactions reveal
causal relationships

7. Pepper’s platform exceeds state-of-the-art target ID
approaches in cancer
12x Better than leading
NLP of over 30M+
scientific sources 4x Better than traditional
multiomic analyses
7

8. 2 key questions in drug development for patients
8
Right target?
Does the target cause disease?
Can regulating the target reverse disease?
Right drug?
Does the drug hit the target?
Does the drug hit something it shouldn’t?

9. Our tech addresses both key questions
9
Understand disease
(What drives or sustains disease)
Understand drug
(Full impact of drug on patient)

10. We can apply our technology to nearly the entire process and can
integrate seamlessly into pharma’s existing processes
10
Target discovery
Lead
discovery
Lead
optimization
Toxicity
Regulatory
filing (IND)
Clinical
trials
Pepper
Pepper
Select most
disease-reversing
target
Select most
effective drug
Predict drug
toxicity
Submit stronger
data package
Stratify patients

11. Platform can be applied across 3 large therapeutic areas
Inflammatory diseases
$98B (2020) | 9.3% CAGR
3 out of 5 people worldwide die
due to chronic inflammatory
diseases.
Oncology
$201B (2021) | 9.7% CAGR
1 out of 6 people worldwide
dies due to cancer.
Neurodegenerative
$34B (2020) | 4.9% CAGR
1 out of 9 people worldwide
dies due to a disorder of the
nervous system.
National Library of Medicine “Nervous system disorders: a global epidemic”; The National Center for Biotechnology Information (NCBI) “Chronic Inflammation”;
United Nations. Department of Economic and Social Affairs “World Population Aging 2019”; World Health Organization “Cancer”
Only 1 out of 50 people
worldwide lives to reach
the age of 80.
11

12. 12
We can generate early revenue while developing our pipeline
Develop drugs internally
Product engine to churn out new drugs
• Strong, fast tech validation
• High value capture
• High control
Develop partnerships
Partner-of-choice for pharma
• High patient impact and access
• Early & recurring revenue
• Robust data & platform validation

13. 13
We’re starting in oncology by looking at 3 cancers worth $5.3B for our
internal pipeline
Addressable population
(US & EU5)
Pricing assumptions
US: $182K
EU: $98K
Total Addressable Market
(US & EU5)
Lymphoma
Myc-driven
8.4K
US: $250K
EU: $93K
$1.5B
NSCLC
EGFRm
(top 4 atypical +
SoC-resistant)
14.8K $2.3B
$1.5B
Liver cancer
Myc-driven
10.7K
Source: Evaluate, UK NHS prices
EU5: France, Germany, Italy, Spain, UK
Top 4 atypical mutations: L861Q, G719X, S768I, E709X

14. We expect to reach the clinic in HCC next year
14
Animals euthanized when tumor above 3000 mm3
Dosing terminated

15. We already
generate revenue
through
partnerships
15
Short-term
total addressable market
(Pre-clinical omics R&D
tech in oncology, neurology,
and inflammatory)
Jumbo-sized platform deals
in the market
(e.g., Roche, Bayer,
BMS, Gilead)
Scalable partnerships
(Low R&D effort)
$3.3B $1B+
Recurring & early revenue
(Embed Pepper into
pharma’s existing
processes)

16. Company Goal Revenue Duration
Top 5 pharma
Mechanism for novel
modality
$100K - $400K 7 months
Public
commercial-stage
biopharma
Target ID for AML $100K - $400K 3 months
Public
clinical-stage biopharma
Mechanism for clinical
asset
$100K - $400K 8 months
TOTAL <$1M
Strong traction with leading drug developers and <$1M in revenue
16

17. Deal sizes expected to increase by orders of magnitude
17
$0M
$20M
$40M
$60M
$80M
$100M
$120M
Current partnerships 2023 Q3+ Late 2024
(drug in clinic)
Upfront Milestones per drug program
$100K+
Upfront
Royalties
Total deal value
-
$100K+
-
$10M - $100M+
Tiered royalties (<10%)
$100M - $1B+
$10M+
$1M+
Upfront
$100M+
$10M+
Deal value per drug program

18. The journey
towards
transomics is
inevitable
Pepper is leading
the way forward
Farther
Closer
Proximity
to biological
function
18
DNA
the early 2000s
(Genomics)
RNA
(Transcriptomics)
2000’s and 2010’s
Proteins
(Proteomic)
present day
Phosphoproteins
(Phosphoproteomics)
the future
Transomics
the future is now

19. Transomics is the future of precision medicine
19
Disease defined
by transomic signature
Future
Disease defined
by tissue of origin
Past
Disease defined
by tissue and mutation
Present
Disease
subtypes
Treatment
options
Patient
response

20. Drive the future of
drug discovery.
jonhu@pepper.bio | www.pepper.bio
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