Lantern Pharma Unveils Innovative AI-Powered Module to Improve the Precision, Cost and Timelines of Antibody-Drug Conjugate (ADC) Development for Cancer
January 27 2025 - 7:55AM
Business Wire
Lantern Pharma Inc. (NASDAQ: LTRN), an artificial intelligence
(AI) company dedicated to developing cancer therapies and
transforming the cost, pace, and timeline of oncology drug
discovery and development, today announced advancements in the
application of its RADR® AI platform to accelerate and optimize the
development of antibody-drug conjugates (ADCs). The global ADC
market is projected to reach $30.4 billion by 2028, growing at a
CAGR of 41.7%, with several recently approved ADCs achieving
blockbuster status with annual sales exceeding $1 billion. Major
biotech and pharmaceutical companies have recently completed
ADC-focused acquisitions valued at over $10 billion, highlighting
the sector's growing strategic importance. Lantern Pharma is
actively advancing multiple ADC candidates through preclinical
development, including a promising collaboration with the
prestigious MAGICBULLET::Reloaded Initiative at the University of
Bielefeld in Germany.
In a peer-reviewed study published in PLOS ONE, Lantern Pharma
researchers demonstrated how their AI-driven approach successfully
identified 82 promising ADC targets and 290 target-indication
combinations, while also validating 729 potential payload molecules
from a screening of over 50,000 compounds. Notably, 22 of these
targets have already been validated in clinical or preclinical
settings, demonstrating the platform's ability to identify
clinically relevant targets. The remaining 60 novel targets
represent significant potential for new intellectual property,
portfolio development of ADC candidates at Lantern Pharma and
licensing opportunities with other biotech and pharma companies.
The ADC module helped to characterize payload molecules with
exceptional potency, exhibiting GI50 values from picomolar to 10 nM
(nanomolar) ranges. These payload molecules can be further
optimized by leveraging RADR’s comprehensive molecular features
database by mapping drug-response relationships with biochemical
and molecular structure characteristics. This AI-driven
optimization capability could potentially enhance both the
selective targeting and therapeutic window of these ADC payload
candidates. Lantern Pharma continues to advance the methods and
automations outlined in the paper as part of it’s RADR™ AI platform
and further enhance the data and computational precision of the
module.
“This breakthrough demonstrates how AI can transform the
traditionally costly and time-consuming process of ADC
development," said Panna Sharma, CEO & President of Lantern
Pharma. "By simultaneously analyzing multiple data types and
integrating mutation profiles with target expression, our team was
able to identify optimal therapeutic combinations that have the
potential to be more effective and safer for specific patient
populations. We believe that our data-driven and machine-learning
ready approach could reduce ADC development timelines by 30 to 50%
and cut associated costs by up to 60% compared to traditional
methods of ADC development."
The research leverages Lantern's proprietary RADR® platform to
analyze complex datasets including transcriptomics, proteomics, and
mutation profiles across 22 tumor types. The platform's ability to
predict mutation-specific responses could enable more precise
patient stratification in clinical trials, potentially increasing
success rates and reducing development costs. This precision
approach to ADC development could be valuable for biotech and
pharmaceutical companies looking to advance their ADC portfolio in
more targeted indications and is also being actively used by
Lantern in the development and modeling of their ADC candidates in
preclinical testing and optimization.
"The implications of this research extend far beyond just
expanding the repertoire of potential ADC targets," said Kishor
Bhatia, Ph.D., Chief Scientific Officer at Lantern Pharma. "By
leveraging our RADR® platform's advanced AI capabilities, we've
created a systematic approach that could dramatically reduce both
the time and cost of ADC development while increasing the
probability of clinical success. Our platform is particularly
well-suited for partnership opportunities with pharmaceutical
companies looking to accelerate their ADC programs or expand their
pipeline with novel targets."
Key Highlights of the AI-powered ADC module include:
- Demonstrated platform validation through the successful
identification of 22 clinically proven targets with established
therapeutic potential
- Discovered 60 novel targets that present significant
opportunities for new intellectual property development, portfolio
expansion, and strategic licensing partnerships
- Developed proprietary mutation-specific targeting capabilities
that enable improved clinical trial design, enhanced precision in
indication selection, and more accurate patient response
predictions
- Established a framework that could reduce ADC development costs
by up to 60% and accelerate development timelines by 30-50% for
both Lantern Pharma and its collaborators
- Created a highly scalable, machine-learning ready approach that
leverages the RADR™ AI platform to systematically evaluate
thousands of potential tumor sub-types and indications
- Designed a clear pathway to commercialization through strategic
industry partnerships and collaborative development programs
The complete research paper, titled "Expanding the repertoire of
Antibody Drug Conjugate (ADC) targets with improved tumor
selectivity and range of potent payloads through in-silico
analysis," is available in PLOS ONE at
https://doi.org/10.1371/journal.pone.0308604. The paper outlines
the approach and initial data-sets used in the development of the
AI-powered ADC development module which continues to be enhanced,
and is being further validated by Lantern Pharma.
About Lantern Pharma
Lantern Pharma (NASDAQ: LTRN) is an AI company transforming the
cost, pace, and timeline of oncology drug discovery and
development. Our proprietary AI and machine learning (ML) platform,
RADR®, leverages over 100 billion oncology-focused data points and
a library of 200+ advanced ML algorithms to help solve
billion-dollar, real-world problems in oncology drug development.
By harnessing the power of AI and with input from world-class
scientific advisors and collaborators, we have accelerated the
development of our growing pipeline of therapies that span multiple
cancer indications, including both solid tumors and blood cancers
and an antibody-drug conjugate (ADC) program. Our lead development
programs include a Phase 2 clinical program and multiple Phase 1
clinical trials. Our AI-driven pipeline of innovative product
candidates is estimated to have a combined annual market potential
of over $15 billion USD and have the potential to provide
life-changing therapies to hundreds of thousands of cancer patients
across the world.
Please find more information at:
- Website: www.lanternpharma.com
- LinkedIn: https://www.linkedin.com/company/lanternpharma/
- X: @lanternpharma
FORWARD LOOKING STATEMENT:
This press release 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 observations in preclinical studies and early or
preliminary observations in clinical studies do not ensure that
later observations, studies and development will be consistent or
successful, (iii) the risk that we may not be able to secure
sufficient future funding when needed and as required to advance
and support our existing and planned clinical trials and
operations, (iv) the risk that we may not be successful in
licensing potential candidates or in completing potential
partnerships and collaborations, (v) 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, (vi) 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 (vii)
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 press release
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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