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ADME Suite

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What is Iktos?

Makya emerges as a groundbreaking user-focused SaaS platform specifically tailored for AI-driven de novo drug design, with a particular focus on Multi-Parametric Optimization (MPO). This cutting-edge tool enables users to generate original and easily synthesizable compounds through a multi-objective framework, achieving unparalleled speed, efficiency, and diversity in results. Featuring a variety of generative algorithms that cater to different phases of drug development—from hit discovery to lead optimization—Makya includes a fine-tuning generator for identifying optimal solutions within your defined chemical space, a novelty generator aimed at uncovering new ideas for re-scaffolding and hit identification, and a forward generator that assembles a specialized library of compounds ready for synthesis using commercially accessible starting materials. The platform's latest addition, the Makya 3D module, markedly enhances both the user experience and scientific functionality. With an extensive toolkit of 3D modeling capabilities for both ligand-based and structure-based methodologies, Makya 3D facilitates the computation of 3D scores that can be effortlessly integrated to steer compound generation within the platform. This comprehensive integration not only refines the design workflow but also provides researchers with profound insights into their molecular architectures, ultimately transforming the drug discovery landscape. As researchers increasingly seek innovative solutions, Makya stands at the forefront, revolutionizing the way compounds are designed and developed.

What is ADME Suite?

Forecasting the absorption, distribution, metabolism, and excretion (ADME) characteristics based on chemical structure is crucial. This set of precise calculations pertaining to pharmacokinetic properties is beneficial for facilitating high-throughput screening of various libraries. Additionally, it offers valuable insights into pharmacological impacts, aiding in the assurance of human safety for the products being developed. Such predictive modeling can significantly enhance the efficiency of drug discovery processes.