First of all, Bhaskar, congratulations on your new role. It's been less than a year since you joined Saama. What led you to take on this position?
Thank you. My background has been in the pharma life sciences space, primarily focusing on digital transformation and harnessing technology to drive innovation. I knew Saama from my previous role at Cognizant, where I saw it as both a competitor and a partner doing exciting things with AI.
My journey into private equity introduced me to a variety of roles. This year, when Carlyle, Saama’s owner, reached out, it felt like coming home. The life sciences sector is something I'm passionate about, and Saama’s transformative work in both the industry and AI aligned naturally with my interests. It made this transition an exciting next step in my career.
2024 has been an interesting year for Saama. Could you provide updates on the new features added to your AI platform, especially those involving generative AI, and how they’re enhancing clinical trial operations?
Stepping into this role, I observed some critical industry dynamics. The pharma sector is grappling with a few significant challenges—regulatory pressures like the Inflation Reduction Act are squeezing revenues, while R&D returns are declining, and development costs are escalating. These factors drive a need for more efficient solutions, and that's where Saama is making a transformative impact by reimagining the way clinical trials are conducted.
We’re harnessing AI as the next S-curve in innovation, transforming not just technology but also operational models. Our AI-powered platform and solutions are helping streamline and accelerate clinical development, moving us away from the traditional, slow, and resource-intensive processes.
Could you give us specifics on how Saama's implementation of AI is fundamentally shifting the approach to clinical trials?
Our core differentiator is our AI and GenAI-powered platform, featuring models trained exclusively for life sciences. It is primarily targeted at end-to-end clinical development, from protocol design to submission. While pharma companies often ask if our platform could extend into other areas, such as market access, we stay focused on clinical development. This enables us to develop robust, specialized solutions that address the challenges specific to clinical trials, ensuring that our platform is purpose-built for optimizing this critical phase of drug development. We do occasionally provide services outside of clinical development, but our primary goal remains revolutionizing this domain.
What have been the main changes in Saama this year, especially since you became CEO?
The industry is shifting, and Saama has adapted to ensure our platform continues to meet evolving needs. We have concentrated on making our platform scalable and user-focused, doubling investments with the support of Carlyle. This involved reinforcing our go-to-market strategy, establishing a customer success team, and enhancing our internal capabilities to attract top AI talent worldwide
Our priority is delivering quality at every stage while maintaining agility to respond to customer feedback. We’ve seen significant progress, evidenced by partnerships with major pharma companies such as Pfizer and AstraZeneca, as well as new collaborations with other large players in the industry.
How are clients reacting to Saama’s AI applications, and what areas do they think could improve?
The response has been positive, though there are general industry-wide challenges in scaling AI initiatives. Drug development is highly regulated, with a risk-averse mindset. Many companies start AI projects, but struggle to scale beyond pilot phases. Successful adoption requires a leadership mandate and a cultural shift toward new ways of working.
Our clients are beginning to see the value AI brings, not as a threat to jobs but as a tool that creates value for organizations and improves patient outcomes. Change management and clear communication on AI’s benefits are crucial in building this confidence.
The AI and pharma intersection is evolving fast. Do you encounter concerns from pharma companies about AI's unpredictability or security, and how do you address these?
Yes, these concerns are valid, especially in a conservative industry like pharma. To address them, we focus on transparency and demonstrate our platform’s capabilities with concrete data points. For instance, our OpenBioLLM model, based on Meta’s open-source Llama 3, consistently shows higher accuracy than similar medical AI models.
This model was notably chosen by Pfizer during the COVID-19 vaccine development, owing to its superior performance, and we continue to showcase these proof points to assure clients of our reliability and commitment to security.
Could you elaborate on your partnership with Pfizer and what it signifies for Saama?
Our partnership with Pfizer has grown, expanding beyond initial studies to cover more areas within the company. This relationship validates the reliability of our platform in a high-stakes environment, showing other pharma companies the tangible value of embracing AI in their operations.
Pfizer’s reliance on Saama as a partner for their critical COVID-19 vaccine project has inspired other companies to follow suit, contributing to broader AI adoption in the pharma industry.
What about your collaborations with CROs? Are they becoming more receptive to working with Saama?
CROs are an important part of our ecosystem. They can leverage the Saama platform to enhance their clinical operations, ultimately delivering greater value to pharma companies. We see the Saama platform as their ‘intel inside’ helping them improve efficiencies and margins. We now have dedicated resources engaging with CROs, establishing partnerships that position them—and us—more strategically in the industry.
Finally, what are your key objectives for Saama next year?
Our primary goal is to support the industry’s shift to embrace AI by listening, engaging, and continuously investing. Listening involves gathering feedback from customers, partners, and industry stakeholders to shape a relevant and adaptable platform. Engaging means being responsive to client needs, showing agility, and solving real-world problems effectively. Lastly, investing in AI research and talent allows us to stay at the forefront of innovation. Together, these priorities form the blueprint for our objectives, shaping our strategy and defining clear goals for every level of the organization as we move forward.
