Simulations Plus Announces Collaboration with Lonza and U.S. FDA to Advance Predictive Frameworks for Complex Oral Drug Products

Key Terms

amorphous solid dispersion medical

An amorphous solid dispersion is a pharmaceutical formulation where a drug is molecularly mixed into a non-crystalline (amorphous) carrier material so the medicine dissolves and is absorbed more readily when taken. For investors, this matters because it can turn a poorly soluble drug into an effective oral product, improving clinical performance, marketability, dosing convenience, and intellectual-property value—similar to dissolving a stubborn powder into a clear gel so it works faster and more predictably.

bioequivalence regulatory

When two medicines deliver the same amount of active ingredient into the bloodstream at about the same speed and level, they are considered bioequivalent. Investors care because bioequivalence is the regulatory test that allows generic or reformulated drugs to replace branded products without new safety trials, often opening large, lower‑cost market opportunities and changing a drug maker’s sales and competitive position—like two recipes that taste the same but sell at different prices.

physiologically based biopharmaceutics modeling medical

A computer-based method that combines measurements about a drug with models of human anatomy and biology to predict how the drug will be absorbed, distributed, metabolized and cleared in different people. Like a weather forecast for a medicine, it helps developers test dosing and safety scenarios on a virtual population before or alongside clinical trials, reducing development risk, time and cost—information investors use to judge a drug program’s prospects and timeline.

in vitro–in vivo extrapolation medical

In vitro–in vivo extrapolation is the process of using results from lab tests on cells or tissues to predict how a drug or chemical will behave in a whole living person. For investors it matters because reliable extrapolation can lower the uncertainty, time and cost of development by helping companies decide which candidates are likely to work or be safe in humans—similar to judging whether a small recipe test will scale up to a full dinner without burning the meal.

Controlled Transfer Dissolution technical

Controlled transfer dissolution is the orderly winding down of a business or legal entity while moving its assets, contracts and liabilities to another entity under a planned, legally supervised process. Investors care because it aims to preserve value and reduce surprises—think of it like handing a running machine to a new operator rather than smashing it and selling parts, which can affect future cash flow, liabilities and the timing of recoveries.

pharmacokinetics medical

Pharmacokinetics is the study of how a substance, such as a drug or chemical, moves through and is processed by the body over time. It tracks how it is absorbed, distributed, broken down, and eventually eliminated. For investors, understanding pharmacokinetics helps gauge the effectiveness, safety, and potential risks of new medications or treatments, which can influence a company’s success and valuation in the healthcare industry.

model-informed drug development medical

Model-informed drug development uses computer models and simulations of how a medicine behaves in the body and in clinical trials to guide decisions about dosing, patient selection, and study design. Like a flight simulator or weather forecast, it helps researchers test scenarios cheaply and quickly, reducing surprise costs and delays; for investors, that can mean faster, cheaper development, clearer milestones, and lower technical and regulatory risk.

AI-enabled technical

AI-enabled describes a product, service, or process that uses artificial intelligence—software that learns from data and makes decisions or predictions—as a core feature rather than a minor add-on. For investors it matters because AI-enabled offerings can boost productivity, lower costs or unlock new revenue streams; like adding a smart autopilot to a routine task, they can change a company's growth potential and competitive edge while also bringing higher upfront investment needs and distinct regulatory or ethical risks.

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Mechanistic modeling approach and experimental integration designed to improve early risk identification, strengthen regulatory confidence, and expand AI-enabled workflows connecting data to decision-making

RESEARCH TRIANGLE PARK, N.C.--(BUSINESS WIRE)-- Simulations Plus, Inc. (Nasdaq: SLP) (“Simulations Plus” or the “Company”), a global leader in model-informed and AI-accelerated drug development that advances biopharma innovation, today announced a funded research collaboration with Lonza Group AG (“Lonza”), a leading contract development and manufacturing organization (CDMO) dedicated to serving the healthcare industry, and the U.S. Food and Drug Administration (FDA) to develop and validate a mechanistic, predictive framework for assessing the in vivo performance of amorphous solid dispersion (ASD) drug products.

“Complex oral formulations such as amorphous solid dispersions present significant scientific and regulatory challenges due to their sensitivity to physiological and manufacturing variables,” said Dr. Viera Lukacova, Chief Scientific Officer of Simulations Plus. “Through this funded collaboration, we aim to integrate advanced in vitro systems with mechanistic modeling to improve prediction of in vivo performance, support regulatory decision-making, and enable more efficient development pathways for these high-impact therapies that deliver faster dissolution and more drug absorption.”

Advancing Mechanistic, Model-Informed Approaches for Complex Products

ASDs are among the most powerful yet complex oral drug delivery systems, with performance influenced by factors such as food intake, gastric pH, formulation composition, and manufacturing processes. Current regulatory approaches often require multiple clinical bioequivalence (BE) studies, which can be resource-intensive while still carrying uncertainty.

The collaboration evaluates whether advanced in vitro dissolution systems—particularly those incorporating dynamic gastrointestinal physiology—combined with mechanistic physiologically based biopharmaceutics modeling (PBBM), can reliably predict key in vivo outcomes, including food effects and the impact of elevated gastric pH conditions.

By establishing and validating these predictive capabilities, the collaboration aims to provide a scientific foundation for reducing reliance on certain clinical BE studies while maintaining the rigor and transparency required by regulators.

Integrating Experimental and Mechanistic Modeling Expertise

The collaboration brings together complementary capabilities across experimental science and computational modeling.

Lonza will lead experimental work, including in vitro dissolution testing under fasted, fed, and elevated gastric pH conditions using advanced systems such as Controlled Transfer Dissolution (CTD), as well as the characterization and, where needed, manufacturing of ASD formulation variants.

Simulations Plus will lead the development and validation of in vitro–in vivo extrapolation (IVIVE) frameworks using its DDDPlus® and GastroPlus® platforms, translating experimental data into predictions of in vivo pharmacokinetics and supporting virtual bioequivalence assessments. At the same time, it creates new opportunities to extend these capabilities into grounded AI-enabled workflow environments, where data, mechanistic models, and simulation outputs will be more directly connected. The Company will also contribute to interpretation within a regulatory context, ensuring alignment with evolving expectations for model-informed drug development (MIDD).

Francois Ricard, Head of R&D, Lonza Advanced Synthesis, said, “This collaboration reflects Lonza’s commitment to advancing more predictive, science-driven approaches as the leader in the field of bioavailability enhancement. By combining advanced in vitro experimentation with mechanistic modeling, and working closely with Simulations Plus and the FDA, we aim to strengthen the scientific foundation that underpins regulatory decision-making for complex oral drug products. Ultimately, this type of collaboration should help accelerate development for our customers requiring bioequivalence during clinical development.”

Alignment with Regulatory Priorities and Industry Needs

This work is supported in part through FDA funding and includes ongoing engagement with FDA scientists to directly align with regulatory priorities to advance MIDD, modernize bioequivalence assessment for complex products, and reduce unnecessary reliance on human studies. By combining regulatory collaboration with open, non-proprietary data and validated methods based on real-world, FDA-approved ASD products, the initiative is intended to inform future regulatory approaches and support broader adoption of science-based alternatives.

“The industry is moving toward a future where decisions are informed earlier, with greater confidence and scientific transparency,” added Lukacova. “Our role is to ensure those decisions are grounded in validated science—while enabling more efficient ways to connect data, models, and insight.”

About Simulations Plus, Inc.

Simulations Plus is a global leader in model-informed and AI-accelerated drug development. We create value for our clients by accelerating the discovery, development, and commercialization of pharmaceuticals and other products through innovative science-based software and consulting solutions. For more information, visit www.simulations-plus.com.

Forward-Looking Statements

Except for historical information, the matters discussed in this press release are forward-looking statements that involve risks and uncertainties. Words like “believe,” “will”, “can”, “expect,” “anticipate,” and similar expressions (or the negative of such terms, as well as other words or expressions referencing future events, conditions, or circumstances) mean that these are our best estimates as of this writing, but there can be no assurances that expected or anticipated results or events will actually take place, so our actual future results could differ significantly from those statements. Forward-looking statements include but are not limited to statements regarding our fiscal year 2026 guidance, revenue growth, anticipated margins and profitability, demand to software and services, the impact of pricing actions, client spending levels, market conditions, the development, capabilities, regulatory acceptance, regulatory compliance and commercialization of AI-enabled and could-based solutions, the timing and content of product initiatives discussed at Investor Day, and our ability to execute our long-term strategic vision. These forward-looking statements are based on current assumptions and expectations that involve risks and uncertainties that could cause the actual results to differ materially from those expressed or implied. Factors that could cause or contribute to such differences include, but are not limited to: effectiveness of our internal operational structure, our ability to maintain our competitive advantages and commercialize AI and cloud-enabled solutions, evolving regulatory and data privacy standards governing AI technologies, acceptance of new software and improved versions of our existing software by our customers, the general economics of the pharmaceutical industry, our ability to finance growth, our ability to continue to attract and retain highly qualified technical staff, market conditions, macroeconomic factors, and a sustainable market. Further information on our risk factors is contained in our quarterly, annual, and current reports and filed with the U.S. Securities and Exchange Commission. No regulatory authority has endorsed, approved, or validated the Company’s products, platforms, or AI-related approaches.

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Investor Relations Contact:
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Financial Profiles
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slp@finprofiles.com

Source: Simulations Plus, Inc.