Biotronics AI Open-Source

Life Sciences & Drug Development — Redefined

Open Source

Biohacking

Artificial Intelligence

GitHub

PharmaSight, an open-source computational framework designed to enable drug repositioning and drug repurposing workflows using commodity hardware without requiring high-performance computing infrastructure. The framework supports a broad spectrum of proteomic, molecular, structural biology, and chemoinformatics file formats, allowing seamless integration into heterogeneous pharmaceutical R&D pipelines. It introduces a novel context-aware similarity computation framework coupled with a kernel-based vector database architecture capable of identifying latent molecular relationships that conventional similarity search methods often do not process. ForenSight (Published), a suite of open-source tools designed to support forensic geneticists and genomics researchers in performing large-scale comparative genetics, DNA matching, and variant-based identity analysis. The framework is optimized for high-throughput forensic workflows, enabling efficient comparison of genetic proles across large datasets while maintaining computational efficiency and reproducibility. In addition, ForenSight addresses one of the most critical challenges in modern forensic genomics: the secure storage and processing of sensitive genetic information. To mitigate biosecurity and privacy risks, the system introduces an encrypted vector database architecture in which raw genetic sequences are transformed into secure, non-reversible representations while preserving their discriminative structure for downstream comparison tasks. MoleSight (Will be published by the end of the June), an open-source molecular modelling framework designed to accelerate computational drug development and pharmacophore research using commodity hardware. The platform enables researchers to perform molecular structure optimization, docking simulations, binding affinity estimation, pharmacophore analysis, and chemistry-driven molecular simulations without requiring specialized high-performance computing infrastructure. The underlying architecture of MoleSight is specifically optimized for efficient physics-based molecular simulations involving protein-ligand systems. Beyond conventional docking workflows, the framework supports multiple operational modes that significantly broaden its applicability. SequenSight (Will be published by the end of the June), a novel open-source statistical framework designed to analyze the physical and structural properties of biological sequences. The platform provides a unified computational infrastructure for DNA, RNA, and protein sequence analysis, supporting a broad range of life science applications, including gene characterization, genomic variant analysis, RNA secondary structure studies, protein folding research, and large-scale multi-omics data exploration. Across all systems, the technologies developed by the team demonstrate strong adoption within their respective domains and continue to evolve toward becoming foundational computational infrastructure layers for life sciences, biomedical research, and secure genomic data processing. Public tracking and verification of these adoption metrics are facilitated through analytics platforms such as Pepy and ClickPy, where users can easily access granular installation statistics and historical data by entering the respective project names directly into the platform search interfaces.