The biotech industry is experiencing a surge of innovation, particularly with the integration of AI and advanced technologies to discover new drugs and treatments. Scala Biodesign, fueled by $5.5 million in recent funding, aims to enhance this progress by refining existing drug candidates, making them more viable through targeted molecular modifications.
Founded on groundbreaking research from the Weizmann Institute of Science in Tel Aviv, Scala Biodesign leverages state-of-the-art protein structure predictions to revolutionize therapeutic molecule engineering. With tools like AlphaFold and RoseTTAfold paving the way, Scala’s founders assert that they can expedite one of the most time-consuming aspects of drug development: optimizing the stability and effectiveness of proteins.
Many potential drugs display useful functionalities yet suffer from limitations that prevent them from being efficiently manufactured or widely distributed—they may degrade at room temperature or react unfavorably in the body's chemical environment. Improving these drugs often involves modifying specific parts of their molecular structure, but determining the ideal changes can be complex.
“Developing proteins is intricate, and even within large organizations, it often involves an element of chance,” explained CEO and co-founder Ravit Netzer. “Scientists frequently rely on random mutagenesis to engineer proteins. However, with today’s knowledge of protein structures, random alterations are not a viable strategy.”
To illustrate, consider a small protein consisting of 100 amino acids, each made up of 20 different options. The combinations of potential variations are astronomical, making it impractical to test every possibility. Consequently, many of these random experiments result in lengthy timelines and exorbitant costs without success.
Scala’s approach resembles selecting a word from a thesaurus rather than randomly picking one from a dictionary, ensuring more coherent outcomes for protein modifications. By merging protein structure prediction with clinical data and insights from naturally occurring proteins, Scala can identify specific adjustments to enhance stability, potency, and manufacturability, thereby transforming nearly-there proteins into valuable therapies.
This entirely computational strategy eliminates the need for wet lab experiments, allowing Scala to generate a small selection of high-confidence synthetic sequences, at least one of which is expected to yield positive results.
A practical application of their technology involved a naturally occurring protein intended for use as a malaria vaccine, which struggled with thermal stability and likely wouldn't endure transport. “Faced with thermal stability challenges, the lab provided one input to Scala and received three optimized options. They chose the best, which is currently in clinical trials,” reported CTO and co-founder Adi Goldenzweig. “While we aim to present one guaranteed solution, achieving complete confidence in our predictions is an ongoing journey. Many others often navigate through tens of thousands of alternatives.”
Goldenzweig emphasized that their process often entails altering dozens of amino acids simultaneously, a rarity in conventional protein engineering, where such extensive modifications are not commonly attempted. “Our range and depth of validation are unmatched, demonstrating that we can achieve substantial improvements across diverse protein applications—from antibodies to enzymes,” stated Netzer. “Our goal is to prove that this process can be successfully scaled beyond academic projects.”
Currently, Scala is collaborating with various pharmaceutical companies and research labs, remaining adaptable with their licensing and business models. Their priority is proving the effectiveness of their technology rather than establishing proprietary biological intellectual property at this point. “As a nascent company, we’re focusing on partnerships and showcasing our technology to streamline collaboration,” Netzer noted.
With $5.5 million in seed funding led by TLV Partners, Scala is emerging from stealth mode and is eager to pursue additional partnerships and studies, all while striving to simplify protein engineering—making it as routine as checking email.
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