Artificial Intelligence-real world applications

InveniAI Introduces New Products to its Pharmaceutical Drug Discovery and Development Suite

11.4.19

InveniAI Corporation, a global leader pioneering the application of artificial intelligence (AI) and machine learning (ML) to transform innovation across healthcare and other industries, today announced the expansion of its flagship AI- and ML-driven innovation monitoring platform, AlphaMeld™ to include products for pharmaceutical drug discovery and development stakeholders. TargetMeld™ and RxMeld™ will be launched at the upcoming Bio-Europe 2019 Conference set for Nov. 11-12 in Hamburg, Germany.

TargetMeld applies machine learning and pattern recognition that broadens and amplifies the possibilities of early innovation. AI-driven insights provide the real-time evaluation of targets and their associations with therapeutic indications by triangulating signals of early innovation from patents, public/private funding initiatives, expert opinions, conference abstracts, and scientific literature. TargetMeld has identified more than 500 emerging targets showing high translational potential to meet clinical endpoints and enables the evaluation of existing targets/drugs for optimal indications. Machine learning analytics provide optimal target-disease combinations that take into account profound associations among novel targets, genes, pathways, and disease pathophysiologies to enhance the probability of clinical success.

RxMeld applies hundreds of disease-specific algorithms and machine learning to recognize successful patterns of emerging clinical innovation across major therapeutic areas. RxMeld identifies and prioritizes the entire pipeline of clinical assets, from preclinical to late-stage and marketed, based on patterns of successful innovation and probabilities of success. Assets are presented so that further innovation, acquisition, or investment allocation is based on a comprehensive assessment of the most appropriate disease indication, drug performance, competition, unmet need, and commercial attractiveness. Currently, close to 20% of the spectrum of clinical assets have been identified in RxMeld with 80% or more probability of clinical success.

CIMeld, previously launched in September 2019 for the biopharma competitive intelligence community, will also be showcased. InveniAI has spent over a decade cleaning, curating, and connecting data sets that are continuously updated and expanded as well as constructing industry and disease-specific machine learning algorithms that form the foundation of AlphaMeld’s suite of products.

“The functionality of AlphaMeld and its suite of products continues to advance at a rapid pace, bringing both power and scale to decision-making,” said Krishnan Nandabalan, Ph.D., President and CEO, InveniAI Corporation. “With AlphaMeld, we are augmenting human intelligence to help stakeholders tap into the vast knowledge found in public and proprietary data sets. Together with our domain expertise, this creates a unique innovation-playground that provides unbiased insights, rapidly translating into actionable products addressing unmet medical needs for patients awaiting efficacious treatment options.”

InveniAI’s CBO, Aman Kant, will deliver his presentation in the Next Generation track on Nov. 12 at 10:20 a.m. CET. He will provide real use-cases of assets in neuroscience and immuno-oncology that have been conceptualized through the platform and subsequently validated with a clinical impact that has advanced as far as human proof of concept.

www.inveniai.com

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