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Nanoparticle Field - At a Glance

Nanotechnology

The use of nanoparticles in medicine is a powerful, but complex and ever-evolving, field. Learn more about the state of the field and how we're tackling common hurdles.

When it comes to drug delivery through encapsulation within nanoparticles (nanoparticle drug formulations), various factors must be considered to ensure their effectiveness and safety. Formulation design involves choosing the appropriate materials, components, synthesis methods and parameters to optimize a nanoparticle drug formulation’s physical properties. The formulation design must address pharmacometrics (i.e. bioavailability, pharmacokinetics, and pharmacodynamics), safety, timed drug release, and stability to maintain the nanoparticle drug formulation’s potency over its shelf life.

Achieving the desired qualities in a nanoparticle drug formation involves a multidisciplinary approach that integrates pharmaceutical sciences, formulation science, and regulatory compliance. Empirical data, obtained through iteration and observations, is vital for Quality-by-Design (QbD) for meticulous formulation design to ensure the quality, safety, and efficacy of a nanoparticle drug formulation. By relying on empirical evidence, scientist can make informed choices about the selection of materials, components, synthesis methods, etc. that directly impact a formulations performance and therapeutic outcomes. pharmaceutical industry.

There are more than 200,000 and growing peer-reviewed publications containing a vast amount of data on the composition, synthesis methods, physical properties of nanoparticle drug formulations and its associated experimental data. ML Insights & Metrics through our nanoML platform makes the global nanoparticle knowledge readily available and accessible.

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Empirical data and data-driven approaches continue to serve as the cornerstones of QbD processes and training AI algorithms that drive drug development and nanoparticle drug formulations. The significance of empirical data allows for hypotheses testing, recreate and validate data in the laboratory, and optimize processes to drive innovation.

Our approach combines QbD principles, big data, and AI for nanoparticle drug formulation design and in silico testing. We help pharmaceutical companies streamline R&D, perform risk assessments, and optimize and tailor nanoparticle drug formulations for target drug delivery to ensure patient safety and efficacy. nanoML changes the paradigm of drug formulation design to accelerate the pace of formulating medicines and multiplicatively increase the number of clinically-approved medicines.