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Coherent Solutions secures strategic investment from IceLake Capital to fuel global growth, push AI innovation, and deliver measurable digital value.

Coherent Solutions, a global digital solutions firm, has secured a strategic investment from IceLake Capital to accelerate its global expansion and enhance its digital offerings. This partnership marks Coherent Solutions' 30th anniversary and underscores its growth potential and proven track record. The transaction is subject to regulatory approvals, and financial terms were not disclosed. Marylebone Capital FZCO acted as the financial advisor, and PBY&A served as the legal advisor.

👩‍🍳 How we use AI at Tech in Asia, thoughtfully and responsibly.🧔‍♂️ A friendly human may check it before it goes live. More news hereAI-designed drugs could be commercially available by the end of the decade, according to Alex Zhavoronkov, CEO of Insilico Medicine.In a Bloomberg Television interview, he expressed confidence that these drugs might emerge within the next five to six years.The pharmaceutical industry is exploring AI’s potential to lower costs and expedite development timelines.However, no AI-developed drugs have received regulatory approval to date.Zhavoronkov noted that Insilico Medicine employs AI at all stages of drug development, from generating hypotheses and optimizing candidates for human trials.🔗 Source: Bloomberg🧠 Food for thought1️⃣ The economics of AI-driven drug development represents a potential industry revolutionThe traditional drug development process costs an average of US$2.6 billion and takes approximately 12 years from discovery to market, creating significant barriers to innovation 1.AI technologies are projected to generate between US$60 billion and US$110 billion annually for the pharmaceutical industry according to McKinsey estimates, while potentially reducing costs by nearly US$100 billion per year 21.These economic impacts stem from AI’s ability to analyze millions of compounds rapidly, predict clinical outcomes earlier, and optimize research resources toward the most promising candidates 1.Insilico Medicine’s progress represents this broader industry shift, with over 450 life sciences companies now integrating AI into their drug discovery processes, indicating widespread recognition of the technology’s transformative potential 3.The financial efficiency gains could fundamentally alter the industry’s risk-reward calculations, potentially enabling more diverse drug development programs and therapies for previously underfunded disease areas.2️⃣ A competitive race is accelerating AI drug discovery timelinesThe prediction of commercially available AI-designed drugs within 5-6 years is supported by the competitive landscape, with at least 18 pharmaceutical companies and more than 75 startups now applying AI in drug discovery 4.Insilico Medicine isn’t alone in advancing AI-designed molecules to clinical trials – Exscientia has already moved AI-designed drug candidates to clinical testing, while Takeda’s AI-selected psoriasis drug is in final clinical testing with results expected this year 45.The industry is seeing various approaches to AI implementation, from companies using it for specific discovery stages to Insilico’s end-to-end approach that incorporates AI from target hypothesis through optimization 6.This competitive environment has accelerated development timelines, with Insilico’s molecule being the first AI-discovered drug to reach phase 2 clinical trials, demonstrating tangible progress toward commercialization 5.The race extends beyond startups, with major pharmaceutical companies like Pfizer and AstraZeneca leading their own AI-driven drug discovery initiatives to avoid being left behind in this technological transformation 7.3️⃣ End-to-end AI platforms represent a fundamental shift in drug discovery methodologyInsilico Medicine’s approach of incorporating AI throughout the entire drug development process signals an evolution beyond the piecemeal AI applications that currently dominate the industry 5.This comprehensive methodology addresses historical bottlenecks in the drug discovery pipeline by using AI to enhance target identification, lead optimization, and clinical trial design simultaneously rather than applying technology to isolated stages 8.Companies employing end-to-end AI platforms can reduce the traditionally fragmented drug development workflow, where different technologies and teams handle separate phases, potentially eliminating efficiency losses at transition points 4.The impact of this approach is evidenced by Insilico’s ability to advance multiple drug candidates simultaneously, with their CEO noting they have “more than 40 programs internally” – a portfolio scale that would be challenging with traditional methods 3.This integrated approach also enables continuous learning across the development process, with data from each stage informing and improving AI models for other phases, creating a compounding advantage for companies that successfully implement this methodology 2