{"id":2103,"date":"2025-09-22T08:31:42","date_gmt":"2025-09-22T08:31:42","guid":{"rendered":"https:\/\/rosetta-omics.com\/?page_id=2103"},"modified":"2025-10-01T13:07:24","modified_gmt":"2025-10-01T13:07:24","slug":"blog-2","status":"publish","type":"page","link":"https:\/\/rosetta-omics.com\/?page_id=2103","title":{"rendered":"Blog"},"content":{"rendered":"\t\t
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Reimagining Oncology: Wahid Awad on AI, Multiomics, Spatial Data and the Shift to Personalised Cancer Care <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/path><\/svg><\/span>\n\t\t\t<\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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Wahid Awad<\/em><\/strong>, Founder and CEO of Rosetta Omics, joined <\/em>Muhammad Younis <\/em><\/strong>for an insightful discussion on the future of precision oncology. He highlighted the challenges of moving beyond standard treatments and the promise of AI, multiomics, and spatial data in delivering personalised cancer care. Wahid shared how Rosetta Omics is advancing predictive models that improve outcomes and reduce costs, while addressing the hurdles to clinical adoption. He also stressed the importance of industry events like the London Biotechnology Show in driving innovation and collaboration across the biotech landscape.<\/em><\/p>

#LBS: Many cancer patients receive first-line therapies that may not be the most effective for\u00a0 them. What do you see as the biggest challenge in making personalised treatment the\u00a0 standard approach? <\/strong><\/p>

Wahid Awad: <\/strong>One of the biggest challenges is the lack of comprehensive, clinically validated predictive tools that\u00a0 can guide treatment selection in real time. Many current approaches still rely on broad treatment\u00a0 guidelines rather than precise molecular insights tailored to individual patients. While multiomics\u00a0 data offers a deeper understanding of tumor biology, its integration into clinical decision-making\u00a0 remains fragmented due to inconsistent data collection, lack of actionable biomarkers, and limited\u00a0 AI-driven solutions for oncologists.<\/p>

At Rosetta Omics, we are tackling this challenge by developing AI-powered predictive models that\u00a0 integrate molecular, and spatial data to provide clinically actionable insights. Our technology\u00a0 enables oncologists to identify the most effective therapy from the outset, reducing unnecessary\u00a0 treatments and improving patient outcomes. However, broader adoption will require stronger\u00a0 regulatory frameworks, reimbursement support, and increased physician engagement to make\u00a0 personalized treatment the new standard in oncology.<\/p>

#LBS: AI, multiomics, and spatial data are transforming cancer treatment by improving response\u00a0 prediction. How do these technologies enhance precision medicine, and what are the biggest\u00a0 obstacles to their widespread adoption? <\/strong><\/p>

Wahid Awad:<\/strong>AI, multiomics, and spatial data are revolutionizing oncology by allowing for a much deeper and more\u00a0 precise understanding of each tumor\u2019s unique biology. Multiomics integrates diverse biological data, genomic mutations, transcriptomic activity, protein expression, and even metabolic pathways providing a complete molecular fingerprint of the tumor. Spatial profiling adds another layer by\u00a0 showing how different cell populations interact within the tumor microenvironment, revealing drug\u00a0 resistance mechanisms and immune response variations that standard tests often miss.<\/p>

At Rosetta Omics, we leverage AI-driven analytics to decode these complex data layers and\u00a0 accurately predict patient responses to specific treatments. Our approach goes beyond\u00a0 conventional biomarker analysis by using machine learning algorithms to identify patterns that might\u00a0 be invisible to traditional methods.<\/p>

However, several barriers hinder widespread adoption, including data standardization, regulatory\u00a0 hurdles, and the need for extensive clinical validation to ensure these AI models are reliable across\u00a0 diverse populations. Additionally, many oncologists require training and confidence in AI-assisted\u00a0 decision-making, which is why Rosetta Omics is actively collaborating with leading cancer centers\u00a0 to integrate our technology into real-world clinical workflows.<\/p>

#LBS: Personalised medicine not only improves patient outcomes but also reduces the cost of\u00a0 ineffective treatments. How do you see advancements in predictive models reshaping\u00a0 healthcare efficiency and affordability? <\/strong><\/p>

Wahid Awad:<\/strong>Precision medicine is fundamentally shifting cancer care from a reactive to a proactive model, where\u00a0 treatment is matched to each patient\u2019s specific tumor profile from the outset. This eliminates trial-and-error prescribing, reduces severe side effects, and prevents unnecessary treatment costs,\u00a0 making healthcare more efficient and cost-effective.<\/p>

At Rosetta Omics, our AI-driven predictive tests empower oncologists to select the right therapy for\u00a0 each patient before starting treatment, leading to:<\/p>