Lantern Pharma : Corporate Overview

Corporate Overview

April 15th, 2024

NASDAQ: LTRN

Forward Looking Statements

This presentation contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section

21E of the Securities Exchange Act of 1934, as amended. These forward-looking statements include, among other things, statements relating to: future events or our future financial performance; the potential advantages of our RADR® platform in identifying drug candidates and patient populations that are likely to respond to a drug candidate; our strategic plans to advance the development of our drug candidates and antibody drug conjugate (ADC) development program; estimates regarding the development timing for our drug candidates and ADC development program; expectations and estimates regarding clinical trial timing and patient enrollment; our research and development efforts of our internal drug discovery programs and the utilization of our RADR® platform to streamline the drug development process; our intention to leverage artificial intelligence, machine learning and genomic data to streamline and transform the pace, risk and cost of oncology drug discovery and development and to identify patient populations that would likely respond to a drug candidate; estimates regarding patient populations, potential markets and potential market sizes; sales estimates for our drug candidates and our plans to discover and develop drug candidates and to maximize their commercial potential by advancing such drug candidates ourselves or in collaboration with others. Any statements that are not statements of historical fact (including, without limitation, statements that use words such as "anticipate," "believe," "contemplate," "could," "estimate," "expect," "intend," "seek," "may," "might," "plan," "potential," "predict," "project," "target," "model," "objective," "aim," "upcoming," "should," "will," "would," or the negative of these words or other similar expressions) should be considered forward-looking statements. There are a number of important factors that could cause our actual results to differ materially from those indicated by the forward-looking statements, such as (i) the risk that our research and the research of our collaborators may not be successful, (ii) the risk that promising observations in preclinical studies do not ensure that later studies and development will be successful, (iii) the risk that we may not be successful in licensing potential ADC candidates or in completing potential partnerships and collaborations, (iv) the risk that none of our product candidates has received FDA marketing approval, and we may not be able to successfully initiate, conduct, or conclude clinical testing for or obtain marketing approval for our product candidates, (v) the risk that no drug product based on our proprietary RADR® AI platform has received FDA marketing approval or otherwise been incorporated into a commercial product, and (vi) those other factors set forth in the Risk Factors section in our Annual Report on Form 10-K for the year ended December 31, 2023, filed with the Securities and Exchange Commission on March 18, 2024. You may access our Annual Report on Form 10-K for the year ended December 31, 2023 under the investor SEC filings tab of our website

at www.lanternpharma.com or on the SEC's website at www.sec.gov. Given these risks and uncertainties, we can give no assurances that our forward-looking statements will prove to be accurate, or that any other results or events projected or contemplated by our forward-looking statements will in fact occur, and we caution investors not to place undue reliance on these statements. All forward-looking statements in this presentation represent our judgment as of the date hereof, and, except as otherwise required by law, we disclaim any obligation to update any forward-looking statements to conform the statement to actual results or changes in our expectations.

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Lantern's AI platform, RADR®, is transforming the cost, pace, and timeline of cancer drug discovery and development

13	5
Lead drug candidates*	Clinical stage lead
powered by AI	drug candidates*

100+	$41.3M**
Issued patents &	Cash/cash eq./
pending applications	marketable securities

2.5 years	$1.5M
Avg. time for new	Avg. cost for new
LTRN programs	LTRN programs
to Ph. 1 Trial	to Ph. 1 Trial

• Includes drug programs being developed in collaboration
• • at 12/31/2023

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*

Current Challenges

Only 6%

of clinical trials using traditional drug discovery approaches succeed

Costly

Risky

Slow

Average cost to bring a new cancer drug to market is $2.8 billion

Out of 20,000 trials from 2012-2022,

19,200 trials failed

Early-Stage development takes 3-5+Years, late-stage development takes 6-12+Years

*Clinical Development Success Rates

and Contributing Factors 2011-2020, BIO Stats

Current oncology drug development is being improved by data-driven, and AI-enabledapproaches and technology

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Lantern is Transforming Drug Discovery Timelines & Costs with AI

AI insights and biomarkers can increase the odds of clinical trial success by 12X*

(*Parker et al., 2021)

RADR® can predict and stratify real-world patients for clinical trials with 88% accuracy

Lantern can compress the timeline of early-stagedrug development by 70% and reduce the cost by 80%

Lantern has launched 10 new programs in 2 years, and has active ongoing ph.1 and ph.2 clinical trials

LANTERN'S DRUG DEVELOPMENT MODEL AND OBJECTIVES

Large Scale/Multi-omics	Proprietary AI	Accelerated
timelines; reduced
Oncology Data	platform RADR®	costs and risks

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Lantern's AI-Driven Business Model has Multiple Routes Towards Success

Areas of Focus

1 Rescue &

Reposition

Drug Candidates

2 Discover

& Develop

New Molecules

Including ADCs

AI Platform

3 Accelerate

& De-risk

Trials with

Biopharma Partners

Successes to Date

Based on previous clinical data and observations, LP-300was rescued for never smokers with NSCLC and is in a Phase 2 trial

LP-284'sunique mechanism of action was predicted by RADR® and was developed to Phase 1 trial in 2 years

Predicting patient response with greater than 88% accuracy, Lantern is accelerating the development ofElraglusib

	High-value
Targeted	Partnering
& Licensing
Clinical Trials	Opportunities

By Lantern and/or other	With biopharma and
biopharma partners	tech companies

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Response Algorithm for Drug Positioning & Rescue

A proprietary integrated data analytics, experimental biology, oncology- focused, machine-learning-based platform focused on drug development

60+ Billion

Data points from oncology focused real-world patient and clinical data and preclinical studies

80%+

Prediction

Success

130K+

Patient

Records

200+

Advanced ML Algorithms

8,163+

Data Sets

AI-Powered RADR® Modules for Oncology Drug Discovery and Development

m1	Discover mechanism
of action of any	m5	Characterize specialized
	compound or drug	attributes of a molecule
	Identify/prioritize a		such as BBB permeability
m2
compound's disease		Enhance the selection
	indications or subtypes	m6
		of optimal combination
m3	Determine optimal		of ADC components
drug combos to improve
	therapeutic potential		Discover drug combos for
		m7
m4	Generate ML-driven	checkpoint inhibitors to
biomarker signatures		improve therapeutic index
	for patient selection

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Lantern Pharma is a Top 10 End-to-End AI Drug Discovery Company

According to Deep Pharma Intelligence (May 04, 2022)

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RADR®'s AI Framework

RADR®'s AI framework develops actionable insights using billions of datapoints

Data sources/Datatypes	200+ AI Algorithms	RADR® Modules (m)
Clinical Trials		Ensemble	m1	MoA Discovery
In vitro/ In vivo			m2	Disease Indication
Studies		Deep Learning		Identification
Genetic			RADR AI insights	Drug Combination
Screens/Panels	Bayesian Based	m3
	Optimization
Chemical Structure			m4	Biomarker Signature
		Tree Based
Collaborator Studies			Generation

Rule Based

Multi-Omics

Drug Response	Clustering

Public/PrivateOthers Repositories

m5 Molecule attribute Characterization

m6 ADC Development

m7 Immune Checkpoint Inhibitor Development

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RADR® Case Study - Actuate Therapeutics

Advanced RADR® machine learning models predict clinical trial patient responses at 88% accuracy

x

• Predicted patient response with greater than
  88% accuracy
• Identified metastatic melanoma patients resistant to PD-1 therapies may benefit from Elraglusib
• Insights and new data including RNA, ctDNA, and protein biomarkers are informing design of an upcoming Phase 2 clinical trial
• Lantern received equity in Actuate as part of the collaboration

Posters:

Lantern is accelerating the development of Actuate Therapeutic's drug candidate, Elraglusib* (9-ING-41), using AI insights produced by RADR®

Model generation for patient response prediction

*Elraglusib is a widely researched GSK-3β inhibitor. Currently, Elraglusib is in multiple active Phase I/II clinical trials as a monotherapy and in combination with other agents (NCT03678883)

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