How AI is Shaping Drug Discovery: LP-300 in Lung Cancer Treatment

Artificial Intelligence-Enabled Drug Discovery is on the verge of a new revolution, with the first data emerging from exciting research indicating that we are rapidly entering a new era. In this exclusive interview, we speak with Dr. Reggie Ewesuedo, Vice President of Clinical Development at Lantern Pharma, about the groundbreaking HARMONIC™ Phase 2 trial. We delve into the promising results of LP-300, a novel therapy that is shaping the future of lung cancer treatment for never smokers.

The Impact of AI in Drug Discovery

Dr. Reggie Ewesuedo, shares insights on how artificial intelligence has played a pivotal role in accelerating drug discovery and improving outcomes for a unique patient population that has long been challenging to treat.

Click the picture to view the PDF version: Pg 32-36.

Could you provide us with the overview of the current statics and trend for both group The unfortunate thing though about lung cancer that is that it remains one of the most common and deadly cancers worldwide?

Dr. Reggie Ewesuedo: This year alone, the American Cancer Society estimates around 234,580 new lung cancer cases, with more women diagnosed than men, and over 125,070 deaths expected. About 85%, of these cancers are non-small cell lung cancer, with adenocarcinoma being the most prevalent subtype. Interestingly, 10 to 20% of lung cancer cases globally occur in individuals who have never smoked, with rates more than double in the Asia Pacific region. 

Lung cancer in never smokers typically appears more in women and at a younger age, presenting unique molecular characteristics and evolution processes that offer opportunities for targeted drug development. While lung cancer in smokers is declining due to public health efforts, the incidence in never smokers is rising, underscoring the urgent need for effective treatments for this group.

Inthe HARMONIC™ Phase 2 trial, you've reported an 86% clinical benefit rate in the initial patient cohort for LP-300, and the objective response rate stands at 43% with notable reductions in tumor sizes. Could you analyze these results in comparison to existing treatments and discuss their potential impact on future clinical practice?

Dr. Reggie Ewesuedo: The preliminary data we've gathered is quite promising.. We've seen an 86% benefit rate, indicating that most patients in the study have not progressed while under treatment. 

This is assessed through three key measures in oncology: the onset, magnitude, and durability of the benefit. Using specific visualization tools like the spider plot, waterfall plot, and swimmer's plot, we can examine these aspects in detail. The spider plot shows a rapid onset of benefits, which are also appearing durable—our second patient enrolled has been on the study for over a year, maintaining response and improving in daily activities.

The waterfall plot reveals significant disease reduction after just three treatment cycles, each 21 days apart, showing impressive responses when LP-300 is combined with standard care. Every patient evaluated after three cycles continued to benefit without any drug discontinuations due to toxicity.

Moreover, the data shows that patients have had between one to four prior lines of therapy. Despite this, even those previously exposed to the standard carboplatin plus pemetrexed regimen have shown remarkable benefits, suggesting that LP-300 in combination with standard care has strong potential, even for those who have failed multiple treatments.

Could you explain how LP-300's mechanism of action interacts with tyrosine kinase inhibitors and affects cancer cells in never smokers?

Dr. Reggie Ewesuedo: LP-300 has been under development for some time, initially with a recognized mechanism of action unrelated to its effects on tyrosine kinase receptors. It’s known to resensitize tumor cells to chemotherapeutic agents by resetting the redox cycle. 

In pivotal trials, never smokers showed significantly doubled benefits from LP-300 compared to others, prompting further investigation into this drug’s additional mechanisms. Subsequent preclinical studies revealed that LP-300 binds to tyrosine kinase receptors—affected by mutations common in never smokers like EGFR, ALK, and ROS, which are pivotal in tumor growth. 

Our findings indicate that LP-300 acts as a multi-tyrosine kinase receptor inhibitor, impacting how these receptors transmit disease-progressing signals. Our study design doesn’t limit the drug to a specific mutation; it suggests that patients with various mutations could benefit from LP-300.

Early data supports this, showing patients with diverse mutations, even complex co-mutations, are benefiting from the treatment which begins to validate our revised understanding of LP-300’s , broad potential in cancer therapyfor never smokers.

How do patient demographics and tumor mutation burden influence the efficacy of LP-300, and what does this mean for personalizing treatment approaches in lung cancer therapy?

Dr. Reggie Ewesuedo: As we develop oncology drugs at Lantern Pharma, an AI-driven company, we continually adjust our approach based on early data interrogation. This has led to significant findings regarding tumor responses in our diverse patient population. 

Our patients show a variety of genomic alterations in tyrosine kinase receptors beyond just EGFR, including complex co-mutations, which supports our understanding of LP-300's broad mechanism of action.

The tumor response, particularly at metastatic lesion sites, is pronounced; metastases often disappear or significantly reduce, suggesting a robust effect of the drug at critical disease sites. The tumor mutational burden, already a part of routine clinical evaluations, appears promising as a biomarker for tailoring treatment strategies. 

This insight aligns with the current shift towards personalized medicine, where we can utilize existing clinical practices to enhance treatment personalization without needing new inventions.

What do you believe the impact of your findings from the HARMONIC™ trial will be on the future treatment of lung cancer?

Dr. Reggie Ewesuedo: When comparing to benchmark data where Peritrexit and Carboplatin were used in similar populations, response rates typically ranged between 20 and 30%. In our preliminary data, we're observing a response rate of nearly double that, at 43%. 

Historically, the median progression-free survival (PFS) with such treatments has been about four to 5.5 months, even with the addition of immune checkpoint inhibitors, which is considered suboptimal. Although it's early and we haven't estimated the median PFS yet, the trajectory we're observing is encouraging.

Discussing the current combination regimens approved with bispecifics, investigators in our study express concerns about toxicity and patient suitability, noting significant discontinuation rates and adverse events. However, our data is competitive; if the current clinical benefits continue , this could play a significant role in treating never smokers with lung adenocarcinoma.

Were there any safety concerns observed during the trial, and how do these compare to typical treatments?

Dr. Reggie Ewesuedo: The FDA and our data safety management board have reviewed our findings, and the safety profile observed matches what is expected with the standard treatments. Most reported toxicities were Grade 1 and Grade 2, primarily from one patient with several comorbidities.

There's no new toxicity, and the treatment has been found to be tolerable with no discontinuations of LP300. This positive safety profile has allowed us to proceed to the randomization stage, which is very encouraging.

As AI continues to play a crucial role in drug development, how do you envision the future integration of AI and machine learning in clinical practice, particularly for oncologists? What are the next steps?

Dr. Reggie Ewesuedo: At Lantern Pharma, we use our RADR® platform to predict patient responses to drugs, including both those under development and others under review. This platform also aids in developing combination strategies for drugsacross various oncology indications.

RADR® utilizes transcriptome data, genomic data, and drug sensitivity data from curated sources, continuously analyzed and updated. This aids in identifying candidates for in-licensing and development and collaborating with other sponsors to devise development strategies. 

This approach has helped us surpass 60 billion data points, enhancing our ability to identify cancer type-specific biomarkers, discover new indications, and add drug candidates to our pipeline to advance cancer therapy. Looking ahead, educating stakeholders, including oncologists, on integrating these tools beyond drug discovery into clinical practice is crucial.