Shawn O'Connor
Analyst · Craig-Hallum
Thank you, and welcome, everyone. We exceeded the top line guidance that we communicated to you last quarter and delivered $24.3 million in revenue during second quarter with growth in both our Software and Service segments. Adjusted EBITDA was $8.7 million, reflecting a 36% margin and adjusted diluted EPS was $0.35, in line with our internal expectations. Turning to the macro environment. We continue to see encouraging market conditions globally, supported by ongoing most favored nation pricing agreements, easing tariff concerns and a more supportive funding environment for our customers. On the regulatory front, the new approaches methodologies or NAMS guidance issued late last year was further clarified with an additional update last month. Against this backdrop, we're seeing a pickup in client spending reflected in solid software renewal rates, increased new logo activity and strengthened service bookings. Overall, we're pleased with our first half fiscal 2026 performance and encouraged by the momentum that it is building across the business. Next, I want to address the broader discussion around artificial intelligence and its impact on software companies, including our own. Over the past quarter, AI-related competitive concerns have weighed on their valuations across most software-based business models, and biosimulation has not been entirely immune to that sentiment. That said, we believe it's important to separate short-term market perception from long-term fundamentals. From our perspective, ongoing advances in AI are a net positive for biosimulation. AI is accelerating the industry's transition to a data-driven drug development workflows and, importantly, enhancing the value of trusted and validated scientific engines rather than replacing them. We have been an early adopter of AI for decades, beginning with the introduction of ADMET Predictor in the late 1990s, and we continue to lead in its practical application today. Beyond using machine learning for property prediction or to improve software development efficiency, we are embedding AI across our product roadmap, improving compute performance, interoperability between scientific engines, data management and duration, automation of repetitive modeling tasks and making our tools more accessible across organizations. While certain software models may face disruption from AI, we believe the core value of our scientific engines, including property predictions, PBPK, PK/PD and QSP modeling functionality and science remains strong and durable. These capabilities are built on decades of scientific investment deep domain expertise, validated methodologies and integration into customer workflows and regulated environments. In contrast to black box approaches, our solutions are trusted, auditable and difficult to replicate. That is why we have long been the preferred choice for commercial drug developers even during a period of significant investment in AI-driven discovery companies, and a number of open source applications. At our Investor Day in January, we outlined the road map focused on further leveraging AI across our ecosystem and we continue to make solid progress executing against that plan. Just a few weeks ago, we announced strategic collaboration programs with 3 large pharmaceutical companies to advance AI workflows across drug development life cycle. The close collaboration between Simulations Plus and leading pharmaceutical organizations will provide direct insight into how AI will be integrated into real-world environments, in forming product direction, workflow standardization and for future commercial models. The programs will utilize Simulations Plus' major software platforms, including GastroPlus, MonolixSuite, ADMET Predictor and Thales. Participating companies will integrate our internally developed AI agents directly into model inform direct development workflows, enabling natural language interaction, automation of data processing coordination of simulations across multiple modeling engines and generation of interoperable outputs from complex multistep pipelines. These programs represent an important step in moving us and our partners beyond experimentation and into practical implementation as we advance our software and services into a unified modeling ecosystem. Finally, it's important to emphasize that our customers are not looking to replace biosimulation engines. Instead, they are looking to enhance their value using AI to improve efficiency, broaden deployment and accelerate drug discovery and development. Furthermore, cost benefits accrue at any point that Simulations Plus can help us simplify and shorten the drug development process or mitigate costly miscalculations. This approach aligns closely with our strategy to be a key partner in our clients' AI journey and supports our long-term growth plans. With that, I'll turn the call over to Will.