Combining Genomics and AI Technologies for Rare Diseases: PhiTech

In line with our goal at Simya VC for 2024 to announce an investment every month, we are proud to share our second investment of 2024, PhiTech.

PhiTech is developing an RNA-based clinical decision support system for rare diseases. It aims to achieve early and more precise diagnosis against diagnosis processes that can take years in rare genetic diseases. PhiTech works to bring the diagnostic power of RNA to clinical practice with bioinformatics (data processing) solutions. Its solution is an artificial intelligence-powered decision support system based on multi-omics data.

Rare Diseases and the Importance of “VUS”

The definition of rare diseases and the number of patients may vary by country and study. Also, the number of patients can vary depending on factors such as the rarity of the disease, difficulty in diagnosis, and lack of recording systems. In Turkey, there are 5 million rare disease patients out of 400 million rare disease patients worldwide. There is no drug treatment in 95% of rare diseases, and it takes an average of 4-5 years to reach an accurate diagnosis. There are diagnostic challenges in rare diseases, such as a less than 50% success rate in DNA-based diagnoses. The existence of approximately 10,000 characterized rare diseases is the primary reason for successful diagnosis to take up to 5 years since most of them have similar or overlapping symptoms. A “VUS” (Variant of Uncertain Significance) is a variant that cannot be classified as pathogenic or benign in genetic samples and, therefore, unusable for diagnosis. This situation poses a serious problem in NGS-based molecular diagnostic methods since many VUS are detected in genetic samples. All these reveal the absence of RNA-based diagnostic solutions and the lack of decision-making software based on the combined power of DNA and RNA in clinical applications. PhiTech is developing a new, more effective, faster clinical diagnostic decision support system based on DNA and RNA sequencing data. This method aims to reach a diagnostic rate of 75-80% for rare diseases.

Multi-Omics Tools and Artificial Intelligence

“Multi-omics” generally refers to the comprehensive and integrative analysis of biological data such as genetics, RNA, proteins, metabolites, and epigenetics. This data helps us understand how biological systems work. According to ARK’s Big Ideas 2024 research, multi-omics tools and technology will reduce research and development spending per drug by more than 25%. Therefore, through multi-omics tools, new markers can be found for diseases, the causes of diseases can be understood, and it may be possible to predict responses to treatment and develop personalized treatments.

PhiTech’s Innovative Approach

PhiTech’s solution includes bioinformatics solutions designed explicitly for RNA-based diagnoses to enable clinical applications. Artificial intelligence will also support their solutions to classify “VUS” variants and increase diagnostic rates. Phi Tech is developing an artificial intelligence-supported clinical decision support system that processes DNA and RNA sequence data.

PhiTech began its studies in the health sector over ten years ago with three academics, founders Saliha Durmuş, PhD., Prof. Tunahan Çakır, and Prof. Erdoğan Sevilgen. After reaching a significant stage in the company, Saliha left academia to work with her team to turn PhiTech into a global brand. About two years ago, they started R&D studies for ~1000 RNA-Seq data from patients and relatives and developed two artificial intelligence-based models to increase the efficiency of diagnostic pipelines. The first one, The Variant Refinement Model, automatically eliminates false positive variants. The other model enables the evaluation of all the variants identified as VUS, typically dismissed in regular pipelines due to their unclassified nature.

Prof. Ahmet Okay Çağlayan, Associate Prof. Emrah Nikerel, Pınar Pir, PhD., and Prof. Mazhar Adli, who represents PhiTech in Chicago, later joined the team and strengthened PhiTech with their academic successes. We are happy to have invested in an innovative product leading the future of mRNA-based research worldwide. We believe the mRNA-based information era has just begun and will lead to groundbreaking discoveries worldwide.

Welcome on board, PhiTech!

Selma Bahçıvanoğlu

Simya VC