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In this episode of the Pharmaceutical Executive podcast, Bill Grambley, CEO of AllazoHealth, explores:

How AI can potentially revolutionize patient engagement and adherence

Utilizing patient-level data and predictive modeling

How AI can identify individual needs and preferences

The importance of ethical considerations and data privacy when leveraging AI in healthcare

Podcasts

Bill Grambley, CEO of AllazoHealth, delves into the potential of AI to revolutionize patient engagement and adherence.

Revolutionizing Patient Adherence: Leveraging AI for Personalized Engagement

AI is transforming content reviews to focus on relevant use, not just generation.

Effectiveness Not Volume: Q&A with Pooja Lal

How to maximize market-entry performance for new pharma products in an increasingly competitive launch environment. 

Using AI to Predict Launch Success

Why a fundamental rethinking of how manufacturers engage with healthcare providers, payers, and patients is necessary in today's pharma landscape. 

Translating ‘Digital-First’ to Commercial Success

The Verseon CEO discusses how this advanced technology is helping to discover new drug candidates.

Deep Quantum Modeling: Q&A with Adityo Prakash

As the physical products we use evolve to become increasingly complex, traditional products liability frameworks may not always fit to provide remedies for harm that can result from using novel product types.

Is Artificial Intelligence a ‘Product’? Products Liability Implications for AI-Based Products

Using AI and RWD to Drive Creative Decision-Making

Pharmaceutical Executive: How do agencies use RWD to drive creative decision making?

A lot of RWD consists of quantitative information. Our database of claims has about 60 million claims in it. If you talk about those as individual data elements, you can get into the trillions. That’s impressive, but it’s meaningless unless someone understands what it is.

Where AI and brand translation comes in is the ability of AI to translate across disciplines. Administrative overhead increases on the amount of resources it takes to run any sort of organization. You must manage huge amounts of information coming in that must be interpreted differently across elements of the business.

A writer that I like compared the invention of AI to the invention of the filing cabinet, which doesn’t sound super exciting. The filing cabinet is not magical, but it enables making the same information standardized and accessible across an entire enterprise. That’s where I think an agency’s ability to translate comes in, and certainly AI will be an empowering factor to this.

I have an example from inside the lab. One of my peers took our full documentation database, everything that we use to educate clients on how to use the reports on our platform and our APIs, and he put a LLM on top of it. He essentially created a search and summarization feature for any question you could think of about how the platform works. That was just a beta test, so we’re not rolling something like that out anytime soon, but it is an example of an agency’s ability to turn analyst reports into a coherent strategy and a set of tactics that will form the creative development and media deployments.

Videos

Ted Sweetser discusses turning information into usable datasets and pulling insights from them.

Using RWD to Create Personalized Engagement

Pharmaceutical Executive: How can agencies harness real-world data (RWD) to drive smarter, more personalized engagement?


 When we think about RWD, we think about claims data and healthcare observations that have been de-identified and rendered HIPPA compliant, but still allow you to get a really fine-tuned understanding about what patient challenges are, what drives decision-making, and what obstacles they may face in obtaining care.

I gravitate towards being able to go past persona-driven strategies where market research is involved much earlier in the pre-commercial or early-launch phases and things are boiled down to broad set of archetypes. We’re able to actually describe those markets in far more detail. That means that agencies should be able to shape messaging that reflects the needs and cares of the given constituency.

We think about this in healthcare in the research side of the business. This includes getting communities to have access to care. There’s a pretty well-established link in getting somebody a healthcare provider that looks like them and is able to reflect their sensitivities and concerns. A notable and unfortunate example of that is the historical record of African Americans reporting pain symptoms and not necessarily being believed by HCPs.

Being able to match the needs of the population with the brands that you’re promoting is an area where RWD can be incredibly essential.

Ted Sweetser discusses how more accurate datasets are solving problems related to getting communities access to better healthcare.

Overcoming Pharma Marketing Challenges with AI

Pharmaceutical Executive: How is AI helping to overcome the challenges pharma marketing teams are facing?


 There’s a brewing issue in the viewability space. For anyone not aware of what that term means, viewability consists of the metrics around validating that a person has seen an advertisement, the time that they’re seeing, and the quality of the placement where a given ad is served. This is something that’s been up in the air since last year when Oracle shut down Moat, which was one of the three major viewability providers. There’s been a lot of talk about the way performance functions in this space for ages. That left IAS and Double Verify as two vendors of this service.

People have objected to things like cutting out large amounts of media inventory that was specifically related to news. Some felt this painting with too broad of a brush in determining what shouldn’t qualify.

There is innovation in this space. There are services leveraging a lot of AI, and one of the more popular trends in recent years of using AI is agentic models that can behave autonomously and crawl across the full span of the internet at a much faster pace and making brand safety decisions that are specific to the needs of an individual brand’s objectives. These models promise to do all sorts of interesting things in regard to shifting what we think of as media and where an impression can be served, hopefully for the better.

It's certainly a big change. It really matters for pharma because, aside from direct response messaging, a huge amount of the spend is going into branding, which has different KPIs than just trying to get a number of clicks on a page. You want to make sure that your message is hitting enough of the population with enough frequency to reinforce the message your brand is putting out there.

Ted Sweetser discusses how the technology is providing greater insight into how marketing materials are being viewed.

How AI is Shaking Up Pharma Marketing

Pharmaceutical Executive: How is artificial intelligence shaking up the pharma marketing space?


 The first top level one that everyone is paying attention to right now (because it’s the most visually engaging) is the ability of art related large-language models to create new forms of content. We saw everyone get excited when OpenAI released an update that allowed users to create Studio Ghibli inspired art, which turned into a meme.

More broadly, people are saying that if they can increase the amount of content that they can generate exponentially by using AI that’s been trained on licensed data sets that are permitted for those uses, there’s a whole world of new, specific messaging to create. That feeds into the personalization, which is a huge part of omnichannel branding, messaging, and building a relationship directly between brands and consumers.

While that’s very exciting in the space generally, pharma is beholden to a higher standard. We’re all familiar with the MLR process of legal review to make sure that everything works. We were at this year’s MM&M Transform conference hearing from a number of creatives about the number of possibilities raised from this space.

A consistent theme was that people can create as much new content as they want, but it still needs to go through thorough vetting to ensure that nothing is being misrepresented about the impact of the drug and that it meets with FDA standards. While it is very exciting, it’s something that’s still further down the line, although it is a factor that agencies are going to be thinking about when it comes to the way that they approach creative.

Ted Sweetser discusses how the technology is expanding the amount of content that can be created.

AI-Powered Heart Scans

As cardiovascular diseases continue to impact a significant portion of the U.S. population, particularly those over 60, the need for timely and accurate cardiac monitoring has never been more critical. However, the shortage of cardiologists and sonographers is creating a significant gap in care. UltraSight’s innovative technology seeks to address this issue by enabling healthcare professionals, including nurses and medical assistants, to perform high-quality heart scans with minimal training. 

sat down with Davidi Vortman, CEO, Ultrasight, to discuss how this technology can help cardiovascular patients.

Pharmaceutical Executive: With cardiovascular diseases affecting 75% of Americans over 60, how does UltraSight’s technology help bridge the gap in timely cardiac monitoring, especially for at-risk patients?

Today, the United States is short 1,600 cardiologists and a similar number of sonographers. There’s a significant gap between supply and demand because ultrasound is the primary diagnostic tool favored by cardiologists. It’s the most accurate and effective choice for assessing cardiac disease.

UltraSight’s technology is helping bridge that gap by enabling any healthcare professional to perform at the level of an expert. We’re training individuals, such as nurses or medical assistants, and within a day, we equip them to consistently perform high-quality heart scans. Today, it typically takes up to a year to become an expert, along with the need for costly mentorship, which is hard to come by.

Expensive investments or outcomes don’t always yield the best results, so we’re eliminating the need for experts to be the only ones capable of performing scans. It’s like introducing a new layer of detection and management that doesn’t exist today.

The U.S. healthcare system faces a significant shortage of cardiologists and sonographers, with about 1,600 unfilled positions in each field, leading to delayed treatment for many patients. Ultrasound, a key diagnostic tool for cardiologists, is bridging this gap by enabling healthcare professionals without extensive training to perform high-quality heart scans. Ultrasight, leveraging AI and deep learning, simplifies this process by guiding users through the procedure with real-time feedback, making it accessible for nurses, medical assistants, and even non-specialists. AI acts as a virtual mentor, providing immediate quality checks and reducing reliance on experts, which streamlines the learning curve and boosts confidence in performing echocardiograms.

Ultrasight has already received FDA 510(k) clearance and CE marking, but broader adoption requires further steps, including building training programs and optimizing workflows, particularly in acute care settings. The company focuses initially on emergency rooms, where rapid cardiac imaging can save lives, enhance triage, and improve patient outcomes. By allowing non-specialists to perform scans, Ultrasight helps reduce delays in diagnosing patients, such as those with syncope, and ensures faster, more accurate triage.

Additionally, Ultrasight's technology is expanding into remote settings. For example, a partnership with Bristol Myers Squibb aims to support patients with cardiomyopathy, allowing remote monitoring of heart health without requiring patients to travel long distances. This decentralization of care enhances accessibility and enables cardiologists to monitor more patients efficiently.

While Ultrasight’s current focus is on cardiology, the technology has potential applications in other areas of medical imaging and diagnostics, but the company remains committed to addressing the significant gap in cardiac care, aiming to improve patient outcomes within the next few years.

Davidi Vortman, CEO, UltraSight, discusses how AI-powered heart scan technology can help high-risk cardiovascular disease patients. 

Video Series

Bridging the Cardiologist Shortage with AI-Powered Heart Scans

Marcel Botha, CEO of 10XBeta, identifies the most significant technological innovations in medical device manufacturing that will be crucial for future pandemic preparedness and supply chain stability.

Crucial Technological Advancements for Future Pandemic Preparedness and Supply Chain Stability

 video interview, Marcel Botha, CEO of 10XBeta, discusses shortcomings in the US' emergency plans for rapid innovation and manufacturing during public health crises, highlighting the need for innovation pipelines, supply chain resilience, and regulatory clarity. He also emphasizes the importance of localized manufacturing, public-private partnerships, and advanced manufacturing techniques like AI and additive manufacturing. Botha notes the success of the Spiro Wave project in reducing ventilator size and the need for better coordination and funding structures. He also advocates for a more agile and collaborative approach to ensure rapid response in future emergencies.

Pharmaceutical Executive: Looking forward, what are the most significant technological advancements or innovations in medical device manufacturing that will be crucial for future pandemic preparedness and supply chain stability?

There are lots of interesting things coming down the pipe. Obviously, it's been two years of AI mayhem. Going from machine learning and large data lakes, to actually have an understanding of where our data can actually have an impact on these LLMs and critical feedback loops with AI tools. AI will play a huge role in everything from biotech to drug development, both discovery orphan drug reuse or repurposement and medical device design.

When I look at AI as a tool to reinforce what we build, it plays a role from the very inception of an idea all the way to regulatory clearance and post market surveillance. It plays a role in how we think about risk and risk analysis, and how we analyze large swaths of data to make sure that we can be risk averse and have a clear understanding of the potential risks outside of just a human assessment. 

Does the machine mean that we don't have a human in the loop? Everything we do, a human has to look and scrutinize what comes out of the trained AI data, but it's advancing at a speed faster than we can learn. It's like when Bill Gates wrote a book, 

 in 1997, which was a comment about how fast we're going to be learning with the age of the internet. This was first.com, and I would say that we are definitely at an age where AI has surpassed the speed of thought.

What is interesting is what type of innovation, opportunities, challenges, objections, or enlightenment we're going to want to get from this. AI is also affecting how we design physical product, how we scrutinize physical product, how we do critical, finite element, and flow analysis. Any tool that we use today can be augmented with an AI layer. Some of them are extremely clunky. I think we're in AI version 1.0 right now, and so I'm very excited to see where we are a couple of generations later, and where it becomes an extension of our intellectual capacity to contribute to the sector.

Anything with data or any physical device that is connected has a data stream, and you can build intelligence layers on top of any data stream. Real time monitoring brings the ability to move a lot of health care to the home, then intelligent systems like AI and ML, that can be run on top of those data streams from those devices in real time, bring the ability to reframe the quality of care. I see a future where we have better care at home than we have in the hospital today. That's an interesting future where we move from a reactive medical industry to a proactive medical industry.

Lastly, we see definitely opportunities for improvement. Beyond AI, there's many other opportunities that we can look up. I've touched on additive manufacturing to death, but we have advanced manufacturing, robotic manufacturing, new chemistries, new polymers, and organic chemistry. 

All of these things will affect how we make products in the future, and all of this is driven by new technologies that are coming on board. We're also seeing a lot of flexible manufacturing approaches. A lot of the sort of collaborative yet competitive, network manufacturing approach that I spoke about in terms of building a resilient ecosystem, from having the tools that can manage the supply chain risk and supply chain response and manufacturing response at a higher than single entity level.

When we have tools, especially with public private partnerships that can assess industry-level flexibility, response, and resource management—especially during disaster relief times—we have an extremely valuable network effect after of technologies and technology companies that can collaborate, compete, co-locate, depending on what season it is. Is it disaster season, or is it Christmas? We need to be able to have that agility, that's what's been missing from the US manufacturing ecosystem for the longest time.

Matthew Yelovich, partner at Cleary Gottlieb, discusses his transition in late-2024 from federal prosecutor to a role at Cleary Gottlieb as well as how he sees the intersection of technology and law evolving in the Bay Area. 

The Evolution of the Intersection of Technology and Law in the Bay Area

 video interview, Matthew Yelovich, partner at Cleary Gottlieb, discusses the appeals of both Theranos founder Elizabeth Holmes and the company’s COO, Ramesh “Sunny” Balwani. The Ninth Circuit recently affirmed the duo’s convictions after considering questions about expert and lay testimony. Yelovich emphasizes the importance of careful vetting of statements to investors and the public, especially in tech-driven companies. The conversation also explores the complexities of sentencing in fraud cases, the importance of corporate governance and accountability, and his transition in late-2024 from federal prosecutor to a role at Cleary Gottlieb.

Pharmaceutical Executive: You transitioned from the US Attorney's Office to Cleary Gottlieb in October 2024. How has your experience as a federal prosecutor, particularly handling the appeal response in this case, influenced your perspective in your new role at Cleary?


: What drew me to Cleary was its top shelf enforcement and litigation practice, which handles some of the most complex challenges that our clients face globally and looks for bespoke solutions to those issues. That was a really enticing practice to join, and it combines that with this incredibly collaborative culture. People are helpful, kind, supportive, and jump in to help with problems and talk through them in a way that is fairly unique in the top shelf firm profile. That combination was really interesting and attractive to me. Coming from the US Attorney's office, one of the things that really makes that work enjoyable is team spirit, where you're collaborating on things, helping each other out, and doing so at a really high level with really complicated problems. I saw some of those same traits in Cleary Gottlieb, so the transition has been terrific. I couldn't ask for better colleagues and better clients, and I'm gratified to be here.

PE: Given your experience in the Bay Area, and your move to Cleary's Bay Area office, how do you see the intersection of technology and law evolving in this region, especially in light of cases like this one?


: This case is an example that the government will not be afraid to bring investigations or enforcement actions in so called fake-it-till-you-make-it situations. Companies would do well to have folks on staff or outside who they're talking to who know the subtleties in this area, the choices technology companies face in this space, and who have credibility with the regulators and enforcement agencies. I think that is a really important part of minimizing exposure and reducing risk at the investigation stage. I see this case as emblematic of the government's approach to this area and enforcement interest on the fake-it-till-you-make-it frauds.

Matthew Yelovich, partner at Cleary Gottlieb, discusses his transition in late-2024 from working as a federal prosecutor to a role at Cleary Gottlieb, as well as how he sees the intersection of technology and law evolving in the Bay Area. 

Matthew Yelovich, partner at Cleary Gottlieb, discusses some of the broader implications for corporate governance and accountability the Theranos case highlights.

Theranos Case Implications for Corporate Governance & Accountability

Pharmaceutical Executive: Given the public interest in this case, what are some of the broader implications for corporate governance and accountability that you believe it highlights?


: Founders and companies would do themselves well to carefully vet their statements to investors and the public to make sure that things line up. In the Silicon Valley and Bay Area, we have immensely talented, amazing, and entrepreneurial companies and founders that are doing great things with technology all the time. That's part of what makes the region so dynamic.

One lesson from this case is there are going to be times when promising technology doesn't work out. That's not a crime. When that does happen, though, the statements and choices you make as a company are really important. Having inside or outside advisors who have some experience in that field can be really valuable. That would be something that companies would be well placed to look into.

PE: You oversaw major corporate fraud prosecutions, including a significant cryptocurrency seizure. How does your experience with these cases inform your understanding of the complexities of modern financial crimes?


: There's really no substitute for spending years working on cases like this, particularly starting on the government investigatory side, in order to inform how you react when you're representing clients in this space and on these types of cases. It has helped me immensely in internal investigation work. You know what to look for, the subtleties of these issues, who might have information, and how to vet important versus less-important issues much quicker having spent years both directly doing and overseeing those kinds of cases.

One thing that I really love about the work I get to do now is Cleary Gottlieb gets to represent folks facing some of their most complex challenges. Having been both involved as a prosecutor doing complex fraud cases, and then as appellate chief overseeing all of our appellate litigation for the United States on complex fraud cases, getting to be on the flip side and dealing with the most complex issues our clients face is a really engaging, intellectual, and rewarding exercise for me.

Matthew Yelovich, partner at Cleary Gottlieb, discusses some of the broader implications for corporate governance and accountability the Theranos case highlights. 

Jennifer Kyle, CEO and founder of Condor, explores how improving financial management directly impacts drug pricing.

How Improving Financial Management Directly Impacts Drug Pricing

video interview, Jennifer Kyle, CEO and founder of Condor, discusses the inspiration behind creating a financial cloud platform for biopharma R&D. During the beginning of her career in auditing and finance, she repeatedly encountered the same financial management challenges across various biotech companies. This led her to develop Condor, a platform that integrates clinical and financial systems, providing a unified system of record for accruals, vendor oversight, budgeting, and forecasting. Future plans include advanced AI and machine learning for benchmarking and deeper integrations with clinical systems.

Pharmaceutical Executive: How does improving financial management directly impact drug pricing?

 Financial management's direct impact on drug pricing is kind of simple. Clinical trial outcomes ultimately affect drug pricing. Prices are set to recover the significant R&D investments before that patent cliff expires. This includes expenses from clinical trials, regulatory compliance, and the high rates of failure. It's not just one clinical trial; it's all of the trials that you've ran—and most have failed in the pursuit of getting it to market. You've got to look at those entire portfolio costs. The higher and less predictable these development costs are, the greater the pressure to set higher prices to achieve that profitability and to ensure funding for future treatments.

Managing your cost is extremely important to be able to recover that revenue. Aside from drug pricing, the predictability of your costs and financing is directly tied to the availability of new treatments. We see this specifically around oncology and rare disease therapeutics. Those programs are very expensive and highly unpredictable. Especially with rare diseases, there aren’t massive patient populations to offset those costs. 

Being able to fail faster for a lesser amount of money, and being able to pivot and adjust, is ultimately paramount for being able to get that drug to market as fast as possible and into the hands of patients that need it.

Jennifer Kyle, CEO and founder of Condor, discusses the inspiration behind creating a financial cloud platform specifically for biopharma R&D. 

Inspiration and Problem Solving: Condor's Core Functionalities

Pharmaceutical Executive: What inspired you to create a financial cloud platform specifically for biopharma research and development? What problem were you aiming to solve?

 I would say I didn't go looking for this, it found me pretty organically. My background is in finance and accounting. I started my career at Ernst and Young auditing a lot of biotech companies and going through IPOs. Initially, I thought I wanted to be a CFO, so I left Ernst and Young and went into the industry to climb the corporate ladder, gain experience, and eventually get that corner office at the top. Along that journey, I realized that I didn't know what I wanted to do.

I was really good at solving problems at the intersection of operations, FP&A, and accounting. I loved making business processes more efficient and effective. I loved to come in, add value, and make things better—that was like my superpower. I saw a lot of companies that had all of these financial projects on  backlog, but didn't really have time in their day-to-day to clean things up. I love doing it and I'm good at it, so I decided to offer my services and help as many companies as I can. That's really where it started.

I got a phone call from a clinical stage, publicly traded biotech company saying they needed somebody to come in to help clean up their clinical accruals. They wanted to use the information to help with some financial planning. Additionally, they had to become 404b SOX compliant, so they needed to step up their internal controls and create a process around compliance. That turned into a comprehensive workbook that connected a lot of the clinical stakeholders and data to the financial and accounting processes, workflows, and compliance. That was such a success at this biotech company that I kept getting called to other biotech companies to go do the same thing.

Over and over, I realized it was the same problem. I wondered if there was any software out there to automate this, because surely there had to be something better than an Excel spreadsheet.

I talked to big pharma companies, small biotech companies, and what I realized was two things: the big organizations build a homegrown database, the small organizations use an Excel spreadsheet, and nobody understands the process. Not the auditors that audit it, not the clinical folks that are managing their contracts and vendors, and certainly not the finance people. I just decided at that point that there's a market for it, and If I didn't build it, somebody else would.

So, I said, ‘Why not? Let's do it.’ That's when my career completely shifted from going from accounting to finance, to business process consultant, to tech entrepreneur, and it's been a really fun ride. Every company is trying to solve the same challenges over and over, and I'm just stoked that we can offer the market some solution here.

Jennifer Kyle, CEO and founder of Condor, discusses the inspiration behind creating a financial cloud platform specifically for biopharma R&D.

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