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and joined the MJH Life Sciences team in February 2023. She attended Kent State University and earned a Bachelor of Science degree in journalism with minors in public relations and creative writing. She enjoys making and listening to music, reading, and spending time with her cats, Astrid and Marceline.

Articles

Catch up on coverage from the first day of the 2024 Elevate-Derm West Conference in Scottsdale, Arizona.

Day 1 Recap: Elevate-Derm West 2024

Maddi Hebebrand is an associate editor of 

and joined the MJH Life Sciences team in May 2024. She attended Baldwin Wallace University, studying Media Production and Film, and is now finishing her Masters in Digital Media through Ohio University. When she's not writing, Maddi loves to read, attend concerts and spend time with her family.

Mark Gimbel, MD, and Whitney High, MD, presented complex cases that underscore the critical need for comprehensive approaches in diagnosing melanocytic lesions. 

Experts Present Cases of Complex Pigmented Lesions at Elevate-Derm West

Roflumilast foam 0.3% significantly improved psoriasis severity, symptoms, and quality of life in patients with moderate to severe scalp and body psoriasis.

New Insights into Roflumilast Foam 0.3% for Scalp and Body Psoriasis: ARRECTOR Trial Patient Reported Outcomes

Apremilast led to a 75% improvement in PPPASI-75 in a significant portion of patients by week 16, with these improvements maintained through week 52.

52-Week Study Reveals Efficacy and Safety of Apremilast for Japanese Patients with Palmoplantar Pustulosis

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Cheever shared with Dermatology Times her excitement for educational opportunities, networking, and presentations from experts in the specialty.

Kicking Off Elevate-Derm West With Eileen Cheever, MPAS, PA-C

Final Thoughts: The Importance of Comparative Studies in AD

Panelists offer concluding insights and emphasize the critical role of comparative studies in advancing atopic dermatitis treatment strategies.

clinical

Video Series

Benzoyl peroxide (BPO) has been a popular topic in both dermatology and consumer headlines within the past week, specifically from news of 

high levels of benzene found in BPO-containing acne products

 such as cleansers and lotions. Valisure, an independent testing laboratory in Connecticut, tested 66 BPO products and found high levels of benzene when BPO products were incubated at 37°C (98.6°F: body temperature), 50°C (122°F: accepted pharmaceutical stability testing temperature) and 70°C (158°F: hot car temperature).

 have been criticized by some, as questions were raised about testing products at such high temperatures. Valisure has been transparent about the reason for the temperatures in their stability testing, writing, “The purpose of stability studies is not to copy the conditions of an average consumer, rather, the purpose is to ensure the product is safe to use for the entire products lifecycle, from manufacturing through distribution to its expiration date, often a total of 3 years for pharmaceutical products. Products must be stable during this entire time and through all the possible ‘bumps’ along the road. It is common to condense the total stability of a product intended for multiple years of use by performing ‘accelerated’ stability studies that elevate the temperature for a few months. For example, according to publicly available calculators, 3 years of room temperature stability is equal to about 169 days at 50°C (122°F). Valisure broadly observed dramatically high levels of benzene in only 18 days at 50°C.”

Valisure also noted that the FDA specifically prefers this testing approach, which is outlined in its 

Christopher Bunick, MD, PhD, FAAD, associate professor of dermatology and physician-scientist at the Yale School of Medicine, has closely followed benzene contamination news in dermatology since the first detection of 

. At the 2024 American Academy of Dermatology (AAD) Annual Meeting in San Diego, California, Bunick presented updates on benzene in BPO to an overflowing room of attendees looking for more information and data. Bunick has no financial disclosures related to Valisure, and is passionate about providing dermatologists with up-to-date information to help better inform their patients.

Bunick began with a history of benzene through academic papers, starting with a German paper from 1936 that evaluated the thermal decomposition of diacyl peroxides, which BPO is a diacyl peroxide. In 1997, Akzo Nobel filed for a patent for the “Reduction of benzene formation in dibenzoyl peroxide formulations.”

“Recently, however, it has been discovered that BPO formulations such as pastes, emulsions, and suspensions based on organic plasticizers, whether in the presence or absence of water, show continuously increasing levels of free benzene throughout their useful lifetime. This free benzene is formed due to the slow decomposition of the BPO over time,” wrote Akzo Nobel.

From their patent application, Akzo also wrote that the minimization of benzene’s formulation is highly desirable due to its known carcinogenic properties.

“Almost 20 to 30 years ago, a company was trying to solve the benzoyl peroxide decomposition problem,” said Bunick.

As a result of these studies, the FDA did complete an investigation, but they did not fully deem BPO safe. After animal testing, it was found that “Benzoyl peroxide is a tumor promoter in several animal species. The significance of this finding in humans is unknown,” a statement that is now added to the nonclinical toxicology section of BPO-containing product’s package label.

USP released a statement on March 8, 2024

, related to the benzene testing from Valisure, stating that benzene contamination should be taken seriously, but that if changes are made to a USP method, complete validation data is needed to prove a product meets USP standards.

“Perhaps the most important line in this entire statement is the next one: ‘It is important to note that USP standards are applicable during the entire shelf life of the product, not just at the time of release,’” said Bunick. “The problem with the USP statement is that the FDA already rejected their methods as not being good enough, and you wouldn’t know that unless you read the FDA’s statement."

In 2020, the FDA rejected USP’s method of gas chromatography- flame ionization detection (GC-FID) for benzene analysis, which is a method that has less precision and accuracy.

The FDA industry standard of gas chromatography-mass spectrometry (GC-MS), which is more accurate, is the method Valisure chose to use in its recent petition.

The findings of benzene in BPO products were validated by 3 different labs using 4 different technology platforms, including GC-MS, GC-HRMS, HPLC, and SIFT-MS. Bunick shared updates that CBS News followed up with the labs, and 2 of the 3 confirmed Valisure’s results when contacted.

“There’s been concerns that superficially when you look at the petition, that it’s all about elevated temperatures. That’s not true. Benzene was also found extensively at room temperature on the shelf/off the shelf. The focus of the petition is stability studies,” said Bunick.

Of the 66 products tested at day 0 at room temperature, 10 of the products had more than 10 parts per million of benzene, and 19 products had more than 2 parts per million of benzene. According to Bunick, the problem with BPO is degradation, not contamination. He also reminded attendees that while the FDA “allows” up to 2 parts per million of benzene, that is 

 if it is absolutely necessary to manufacture said product. Bunick added that with so many other acne treatments available, it is not absolutely necessary to manufacture BPO with such unsafe levels of benzene, even at 2 parts per million.

Stability testing is not meant to replicate consumer use or “real-world” use, it’s intended to evaluate the full, 3-year product “life cycle.” 3-year stability at room temperature is equal to 169 days at 50°C or 122°F which is based on industry standards. It is a regulatory requirement to perform stability testing on products and should be conducted on products under normal storage conditions, or, preferably, under exaggerated conditions, according to the FDA.

However, in some cases, stability testing does overlap with real-world outcomes. Bunick shared new data for the first time today that demonstrated that of 5 BPO products tested at 37°C (98.6°F), or human skin temperature, 1 product had more than 10 parts per million of benzene, and all 5 had over 2 parts per million of benzene.

When considering Valisure’s testing, Bunick pointed out that every time Valisure detected a carcinogen in consumer products, some form of a recall followed.

Bunick noted that many people have questioned who is Valisure. Valisure is a company hired by the United States Department of Defense to check the quality of drugs for the United States military. Their number one funder is drug purchasers, according to Bunick, because these companies want to know what they are buying is safe.

Bunick wrapped up his session by reviewing recent benzene studies and news items, all of which called out benzene’s associated risk with various cancers such as leukemia. Regulatory agencies such as the CDC, WHO, EPA, and NOSH have all made similar statements that benzene is a known human carcinogen.

December 2023, the FDA released new guidance for industry

 for the reformulation of drug products containing carbomers manufactured with benzene. The FDA has also proposed a ban on 

hair-straightening products containing formaldehyde

, another carcinogen, with the proposed ban expected in April 2024.

“So, what does this all mean and what am I going to advise for patients? I will say we as a community have to see what is validated. I do not necessarily think at this moment that no one should use benzoyl peroxide. I think there has to be a proportional response until more data comes out,” said Bunick.

He concluded, "With Valisure’s agreement, that for those providers and patients who wish to continue benzoyl peroxide-containing products, that a proportional response at this time would be to keep the product refrigerated at all times, renew the medicine every 3 to 6 months, and avoid heated storage. This will not necessarily eliminate all benzene, but should slow its decomposition. This measure gives the medical community a chance to await further investigation and recommendations.”

At AAD 2024, Linda Stein Gold, MD, added in a statement to 

: "Benzoyl peroxide has been a staple in our acne treatment armamentarium. We take the recent information regarding benzene very seriously. This warrants a thorough review to understand the potential implications."

The importance of stability testing. News release. Valisure. March 6, 2024. Accessed March 11, 2024. 

https://www.valisure.com/valisure-newsroom/the-importance-of-stability-testing

Bunick C. Discussion of new findings in benzene in BPO-containing products. Presented at: 2024 American Academy of Dermatology Annual Meeting; March 8-12, 2024; San Diego, CA.

Benzoyl peroxide (BPO) products have been found to contain high levels of benzene, a known carcinogen, when subjected to stability testing at elevated temperatures. Valisure's findings, validated by multiple labs, have sparked debate over testing methods and the safety of BPO products. The FDA has not fully deemed BPO safe, citing its potential as a tumor promoter. Experts recommend cautious use of BPO, suggesting refrigeration and frequent renewal to mitigate benzene exposure. Regulatory bodies continue to address benzene's risks, with ongoing investigations and potential reformulations.

Christopher Bunick, MD, PhD, presented updates and new data on the recent news of benzene found in benzoyl peroxide products. 

Updates on Benzene in Benzoyl Peroxide Products at AAD 

“Rare Disease Day raises awareness for the 300 million people living with rare diseases around the world and their families and carers. Relatively common symptoms can hide underlying rare diseases, leading to misdiagnosis and [delayed] treatment,” writes the 

Rare Disease Day has been observed globally every year on the last day of February since its creation in 2008. This year, Rare Disease Day is observed on February 29, and it is an opportunity to work toward increased awareness.

One of the emerging methods for further studying, analyzing, and detecting rare diseases and their characteristics is through artificial intelligence (AI).

Joseph Zabinski, PhD, MEM, the managing director of AI and personalized medicine at 

OM1, a real-world data, AI, and technology company with a focus on chronic diseases

, and Stefan Weiss, MD, MBA, FAAD, the managing director of dermatology at OM1, exclusively share their expertise into AI’s capabilities in dermatology and specifically, rare diseases such as generalized pustular psoriasis. Zabinski and Weiss also address the common concern of with so many AI platforms available: How can clinicians trust AI’s data and learn from its insights?

Navigating Rare Dermatologic Diseases Using AI

There are a few issues that come up when we are trying to understand rare dermatologic diseases from the data access perspective and the patient journey perspective. The first is that patients with rare diseases tend to languish for long periods of time, sometimes going years without a diagnosis or having been misdiagnosed in another disease category. In both cases, this means we cannot access those patients’ data as far back in the record as we would like to so we can see where they began their disease states until they reach an accurate diagnosis. However, this is an area where having AI tools to help us look for undiagnosed or misdiagnosed patients can be helpful. Another point with respect to data accessibility is that in a lot of conditions that are more common, there are sometimes rare subtypes of the disease that may be hiding in large populations and in large datasets. Unless we have good tools that can pull out and isolate the patients who belong in those rare subtypes, they can get lost in the noise. It is not something you worry about so much with larger disease states where population average characteristics may be more important, but certainly, in the rare disease instance, it is quite important.

OM1’s Patient Finder is quite an exciting tool. It does what it says: find patients. It is built using our digital phenotyping AI technology, PhenOM. We can use PhenOM to understand patterning and signaling information in patients’ data histories, just like we might understand a patient’s genetic code by using genotyping, for example. If we can lay out the information in those patients’ histories and then use this digital phenotyping technology, we can ask, “What are some of the data elements that are unique for this patient and perhaps associated with a characteristic or an outcome of interest that that patient also has in their record?”

In the case of rare disease, we might collect a group of hundreds or thousands of patients with a rare disease and ask, “Using this technology, what data characteristics were present in this patient’s past before they reached a point of diagnosis that may have signaled that that’s where they were headed?” In other words, could we detect early warning signals? Patient Finder compresses those sets of signaling information into digital phenotypes; I think of them as fingerprints. Once we have the fingerprint for the disease, we can then compare new patients’ records to it.

This is where Patient Finder is powerful in deployment. We can use it to look at health system data and we can use it to look at other novel datasets, but once it understands that reference fingerprint, we have the ability to call out patients who are highly likely to match that fingerprint, meaning they are highly likely to have the condition that we’re looking for, even if they haven’t been diagnosed yet. By being able to call them out we can study them further, or, in clinical implementation, patients can be contacted, and if they consent, can proceed with diagnostic evaluation and potentially receive a diagnosis.

Improving Data Collection of Undiagnosed Conditions

Patient Finder works hand in hand with some of the other efforts that we work on at OM1 to gather data, improve the quality of data, and, ultimately, give us insight into where patients with rare diseases are, how they might more quickly be diagnosed, and then, if appropriate, be offered treatment for their condition. The first of those ways is to use Patient Finder’s ability to look at a dataset and ask, “Who are and how big is the population of patients hiding below the surface of this dataset who may have the condition that we are interested in finding?” It is often the case, at least if we are talking about a rare disease with dedicated diagnostic coding, that we can find some patients in a dataset. However, we also have a hypothesis that there are others, as I describe them, beneath the surface who have similar clinical characteristics in their background, but who are not yet labeled with a code that lets us easily filter the dataset to find them.

Patient Finder can look at a dataset and say, “In addition to the few thousand people that you found, here are another 500 who are highly likely to also belong in that population.” That capability can do useful things such as giving us a better sense of true disease prevalence. Sometimes this is useful in a clinical trial context. Recruitment is a significant challenge in trials, and the ability to point to places where patients who may have been missed are concentrated can be helpful for recruitment efforts and figuring out how to optimize site selection.

The other way that Patient Finder helps with understanding and improving data gathering and processing for rare diseases is in the context of more proactive data gathering. This is another concept we spend a lot of time on at OM1: constructing digital registries, which can be interesting in the rare disease context. Patient Finder can help us by saying, “As the patient moves along in their journey, it is possible that early on in their journey, they have some indications that they may be on the path to a certain outcome, a certain progression, or a certain diagnosis.” We may not be sure yet, but Patient Finder can give us a sense as they progress of how their likelihood is changing. Is their path converging toward something of interest to us with respect to the clinical outcome? Or is it bending away from that? The ability of Patient Finder to say, “At this moment in time, for this data stream I am looking at, these patients look similar to the target group that I care about” is quite a powerful application in enhancing data availability for patients with rare diseases.

AI’s Role in Improving the Lives of Patients With Rare Diseases

There are a couple of things that I have learned in my career by working with people impacted by rare diseases and trying to understand them better to develop treatments. First is that each rare disease is unique. Of course, there are relationships among various rare diseases, but with somewhere close to 7000 rare diseases, they remain remarkably different from one another. This is true clinically and is also just as true at the data level when we are trying to understand what is going on with patients in the data. It is true with AI as well; just because you have a model that does well in one rare disease does not mean that the same thing will work well in another rare disease. That is why our whole digital phenotyping approach is designed to go one level deeper than just point-solution modeling. It is designed to say, “We can reflect what is true about the patient and their data characteristics.” Then we can use that greater flexibility to understand different rare diseases through pattern matching, again just like we might first understand a patient’s genetics, and then look for specific disease-associated mutations. I do think that both AI and data can be quite helpful with better understanding rare disease patients’ trajectories and ultimately getting them better treatment if we can be more precise in distinguishing them from everyone else.

This is one of my personal areas of focus, this notion that rare disease patients get lost so often in larger disease populations. They may have certain symptoms of a rare disease and go to see their primary care provider, have some testing done, and eventually receive negative results, so they go back to their primary care provider, or they go from specialist to specialist without answers. That kind of pinballing around can take years from patients’ lives. If we can reach a nice visibility into what a patient journey looks like and use AI to point out patients who are somewhere along that journey, we can be much more impactful. We are being much more impactful in clearing up some of that long-term dragging out of the process and getting patients at least to the point of being treated by a specialist and having access to available treatments much more quickly.

AI is certainly a buzzword, and it’s not always positive. If we read the popular press headlines these days, most are about problems with AI. They are about privacy violations, instances where AI has made incorrect predictions, and those have resulted in bad real-world consequences. This is one reason we are much more conservative in health care with respect to using AI than in some other industries. That said, there is a real path toward trust with AI tools. If we can establish that trust, AI tools can accomplish impressive improvements all over the world as it is today.

The first thing I focus on is contextualizing what AI can and cannot do. In a clinical treatment context, AI is a helper tool. It is not a decision maker that replaces clinicians. It is something that should be able to provide some additional insight and additional personalized vision for providers at the point of care to the patient sitting in front of them. AI can say things such as, “This patient looks like they are at an elevated risk of having XYZ condition, or they may be more likely to respond to this treatment or more likely to have a negative reaction.” You may want to consider those findings in your conversation with the patient. That is the appropriate application for AI tools today.

The other consideration is, and this is something we have built into Patient Finder and the underlying PhenOM technology, the ability to explain why AI says what it does. Many people have experimented with ChatGPT and other large language model tools. It is amazing the kinds of answers these tools generate, but it is mysterious to think about how they produce these answers. And I do not think it is obvious, even in many cases for experts, how the model came up with the output it produced in any specific instance. We focus on explainability for our tools like Patient Finder, by which we mean the ability to sit down with clinical experts who know the disease but do not know the AI part and say, “These are the factors that pointed the model in this direction.”

It is not the same thing as saying there is a smoking gun, that if the patient had a twitching left eyelid and a rash on their thumb, then they have this very specific condition. It is not that simple or straightforward. That is another myth that gets caught up in the AI hype. However, when you can have a conversation and say, “This is what this patient’s phenotypic profile looks like. This is how it is different from others, and that is why the model pulled this patient out of the broader pool,” I found that to be quite an effective way of building trust with clinicians helping them see how AI can integrate into their practice.

I keep hearing that 2024 is the year that AI grows up. We will see if that is true; we can check in again in January 2025. But I think and I hope that there is an opportunity now, perhaps through the popularization of AI, for it to have a mature impact in the coming months and years, especially in areas that are often neglected, such as rare diseases.

, is the managing director of artificial intelligence and personalized medicine at OM1.

Revolutionizing GPP Recognition Through Data Collection

The American Academy of Dermatology’s (AAD) DataDerm is the largest single registry of dermatology patients in the country, which forms the foundation for any data analysis that can be done within dermatology at OM1. OM1’s Patient Finder, in its purest form, is the ability to identify individuals who may suffer from a disease but lack awareness that they carry it. As such, it can identify an individual who may not present with the disease until later in life. Patient Finder can also identify individuals who may perform better or worse on a certain therapeutic in terms of either efficacy or safety. As it relates to generalized pustular psoriasis (GPP), deploying Patient Finder was an opportunity to focus on individuals who have a rare disease, GPP, that often goes undiagnosed or misdiagnosed for a very long time.

For background on GPP, these individuals tend to present with pustules all over their body. As many do not know to see a dermatologist, they will often find themselves in urgent care or in the emergency department, which could spiral into a hospital admission and extensive use of antibiotics. Identifying in advance those individuals who may carry GPP offers the opportunity to be more proactive about care delivery, either connect with a dermatologist proactively or at least recognizing that should a flare occur, informing the rendering provider that neither hospitalization nor extensive antibiotic use is necessary. The partnership between OM1’s Patient Finder and AAD’s DataDerm for GPP is really an opportunity to drive improvements in patient care.

There are some dermatologic diseases that we all can recognize from 100 yards away. However, many are hard to distinguish, especially for the non-dermatologist. Recognizing the individuals who are more likely to carry and present with a certain disease can be extremely helpful. The best example of another dermatologic condition for which Patient Finder would be useful is hidradenitis suppurativa (HS), a disease where cysts form under the breasts, in the groin, or under the arms. When these cysts form as a one-off, individuals often find themselves in a primary care office. Women quite frequently go to their gynecology clinic. Many patients visit urgent care to have the cysts lanced. However, cyst removal is not going to treat the underlying condition. If we can identify in advance those individuals as suffering from HS, we are better able to connect them to the health care system for appropriate treatment.

One of the main challenges of diagnosing and treating GPP is finding physicians who recognize the disease. GPP is a rare disease and like all rare diseases, it is quite infrequently seen by even by the specialists who may treat it. By leveraging large datasets to identify carriers of the disease, those individuals can be better managed.

Rare diseases, dermatologic or otherwise, are rare, and therefore hard to recognize, diagnose, and treat. If we can use AI for identification, we can improve the care that those people receive.

In medicine, there is hesitancy around AI because of the concern that the “machine” will take over from the human.

Because AI sees patterns more rapidly, it has been highly leveraged in pathology and radiology. Despite the visual nature of dermatology, there remains the need in dermatology to understand the whole patient. A single picture of a red itchy plaque on the elbow may be eczema, it may be psoriasis, it may be fungal-related. In the end it can be the manifestation of many different diseases. It is challenging for the machine to make that determination without having greater context. Thus, AI is not there to take over the role of the clinician, but rather to help and improve patient care.

If AI can determine that patient X would do better on drug A than drug B in terms of either safety or efficacy, then it is a valuable tool in finding the right patient the right drug at the right time. That is the way AI should always be regarded within the clinical arena.

, is the managing director of dermatology at OM1.

1. Rare disease day. Rare Disease Day. Accessed January 17, 2024. 

2. What is a rare disease. Rare Disease Day. Accessed January 17, 2024. 

https://www.rarediseaseday.org/what-is-a-rare-disease/

Share your experiences with treating rare dermatologic diseases by emailing 

Rare Disease Day aims to raise awareness for the 300 million people affected by rare diseases globally. Artificial intelligence (AI) is emerging as a valuable tool in identifying and diagnosing rare diseases, such as generalized pustular psoriasis (GPP). OM1's Patient Finder, utilizing digital phenotyping, helps identify undiagnosed patients by analyzing data patterns. This tool enhances data collection, improves diagnosis, and aids in clinical trials. AI's role is to assist clinicians, not replace them, by providing insights into patient care and treatment options, fostering trust in AI applications.

From the February cover: Joseph Zabinski, PhD, MEM, and Stefan Weiss, MD, MBA, FAAD, share their expertise into AI’s capabilities in dermatology and specifically, rare diseases such as generalized pustular psoriasis.

Rare Disease Detection With AI: What Tools to Trust

Implementing Photodynamic Therapy to Improve Patient Outcomes

Video content above is prompted by the following:

Do you have a specific example to share of a successful use of PDT and background on that patient success?

How can the increased use of PDT impact patient satisfaction and practice outcomes?

Photodynamic therapy (PDT) has shown promise in treating various cancers, including non-melanoma skin cancers, esophageal cancer, and certain lung cancers. A notable success story involves a patient with early-stage esophageal cancer who achieved complete remission following PDT. The increased use of PDT can enhance patient satisfaction by offering a non-invasive, targeted treatment option with minimal side effects. Additionally, it can improve practice outcomes by reducing recovery times and hospital stays, ultimately leading to cost savings and better resource allocation within healthcare facilities.

Anthony M. Rossi, MD, highlights a successful case of photodynamic therapy (PDT), provides background on the patient’s outcome, and explains how increased use of PDT can enhance patient satisfaction and improve practice outcomes.

Yes, I diagnose and treat psoriasis through telehealth. 

Yes, I diagnose but will not treat psoriasis through telehealth.

Yes, I will treat psoriasis through telehealth but only established patients.

No, I do not diagnose or treat psoriasis through telehealth.

The use of telehealth in hospitals grew from 35% in 2010 to 76% in 2017

, and since the COVID-19 pandemic, that number has likely increased. Do you diagnose and/or treat psoriasis through telehealth appointments?

Fact Sheet: Telehealth. American Hospital Association. Accessed August 24, 2023. 

https://www.aha.org/factsheet/telehealth#:~:text=Telehealth%20connects%20patients%20to%20vital,place%2C%20at%20the%20right%20time

Telehealth adoption in hospitals surged from 35% in 2010 to 76% in 2017, with further increases likely post-COVID-19. This growth reflects the expanding role of telehealth in diagnosing and treating conditions like psoriasis. The pandemic has accelerated the integration of telehealth into routine healthcare delivery, offering patients timely access to care. The American Hospital Association provides resources and data supporting telehealth's efficacy and its potential to enhance patient outcomes by connecting them to necessary healthcare services efficiently and effectively.

Polls 

POLL: Do You Diagnose and Treat Psoriasis Through Telehealth Appointments?

All 3 drugs listed in this poll have recently made appearances in the news for various reasons.

Moderna and Merck recently announced follow-up data

 from the phase 2b randomized KEYNOTE-942/mRNA-4157-P201 study, a clinical trial evaluating mRNA-4157 (V940), an investigational individualized neoantigen therapy, in combination with pembrolizumab (Keytruda), Merck's anti-PD-1 therapy, in patients with resected high-risk melanoma (stage III/IV) following complete resection.

V940 plus pembrolizumab also continued to demonstrate a meaningful improvement in distant metastasis-free survival, compared with pembrolizumab alone, reducing the risk of developing distant metastasis or death by 62%.

Moderna and Merck's phase 2b study of mRNA-4157 (V940) with pembrolizumab shows significant improvement in distant metastasis-free survival for high-risk melanoma patients. AiViva Biopharma's phase 1/2 trial of AIV001 (Axitinib) presents promising results for basal cell carcinoma treatment, potentially offering a non-surgical option. Checkpoint Therapeutics faces a delay in cosibelimab's approval due to manufacturing issues, not clinical data concerns. The company plans to address these deficiencies and anticipates approval in 2024.

Click here to answer this week's poll about a recent FDA Complete Response Letter.

Eileen Cheever, MPAS, PA-C

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