AI-Driven R&D Solutions for the Next Era of Discovery

AI-driven R&D is the digital transformation of scientific research and development, shifting from traditional human-driven, trial-and-error processes to AI- and data-driven, closed-loop experimentation. 

With the SDLabs platform:

• Define parameters and objectives within your design space.
• Our algorithms recommend the next best experiments.
• Experiments are executed, manually, with robotics, or in simulation.
• Data is centrally managed and analyzed in real time for insights.
• The ML model continuously retrains with new data, feeding back into the decision-making process for ongoing optimization.
• This approach shortens discovery cycles, boosts productivity, and helps you reach optimal solutions faster.
  

SDLabs accelerates discovery and optimization across industries such as pharma, biotech, materials science, chemistry, cosmetics, energy, and food. By reducing experiments from thousands to hundreds, it enables faster breakthroughs, lowers costs, and makes complex, multi-objective optimization problems solvable.

No, SDLabs is a no-code AI platform with a user-friendly interface. Users do not need to be familiar with coding or machine learning to use SDLabs. The platform offers a library of  ML optimizers, so you can choose to deploy our proprietary algorithms, open-source options, or your own.

No, you can start experiments from scratch or preload historical data  to give the AI an initial head start.

SDLabs offers multi-objective optimization (also known as Pareto optimization), allowing you to optimize multiple objectives simultaneously. For example, you can maximize yield and selectivity while minimizing cost, at the same time.

Absolutely. Since SDLabs explores the full design space using Bayesian optimization, it can reveal unexpected relationships and trade-offs between parameters, thereby uncovering optimization opportunities you might not have considered in traditional trial-and-error approaches.

● Complex Experiment Design & Optimization: Find the global optimum in vast search spaces, using an AI-driven Design of Experiments (DoE) approach, whether in synthesis, formulation, catalysis, or process optimization.

● Time and resource constraints: Achieve results up to 10 times faster and more cost-effective than traditional methods.

● Lack of Machine Learning Expertise: Our user-friendly, no-code interface means users don’t need coding or ML knowledge. No technical barriers.

● Data Management & Integration Challenges: SDLabs centralizes data and offers seamless integration with robotic platforms and existing data management systems like LIMS and ELNs.

Yes. Atinary’s SDLabs platform is hardware-agnostic and integrates seamlessly with robotic platforms (eg. IBM’s RoboRXN, Chemspeed, and Unchained Labs) and software like LIMS and ELNs. Our cloud-based platform, hosted on AWS, ensures secure access, and API/SDK options enable custom integrations.

Yes, Atinary’s AI platform, SDLabs, is highly adaptable and designed for broad applicability across numerous industries and research areas. Our deep tech is made broadly accessible through our no-code approach.

The SDLabs platform is a general-purpose solution for optimization challenges across:

● Pharmaceutical and Biotech: Pre-clinical and early-stage R&D from small to biologics.

● Materials Science: Batteries, solar cells, catalysts, new materials.

● Chemistry: Catalysis, synthesis, and process optimization.

● Cosmetics, Flavors and Fragrances: Molecular discovery, sustainable formulation, screening, and method development.

● Energy Technologies: Chemistry and materials for batteries, perovskites, solar cells, and carbon capture technology.

● Food and Ag Tech: Food R&D, formulation, flavors, and agricultural chemistry.

● And many more.