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CCC Releases AI-Enabled Affiliation Matching Software Powering Open Access Publication Modeling and Analysis for Publishers

Copyright Clearance Center

The solution combines sophisticated, AI-enabled, affiliation-matching technology and analytic capabilities, to reliably disambiguate institution affiliation and funder relationships. CCC is an active partner in the evolution of OA publishing models. CCC will showcase its new agreement modeling capabilities at the Frankfurt Book Fair.

Training 118
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The Power of Healthcare Data Analytics

LEVO Health

Practices can use healthcare data analytics to gain insights that can transform their marketing efforts in the digital age. Data analytics is the process of collecting and analyzing data to make informed decisions. Unfortunately, many healthcare practices are still in the early stages of adopting and fully utilizing data analytics.

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Lung Chip Mimics Radiation Injury

Medgadget

Researchers at the Wyss Institute at Harvard University have developed a microfluidic chip that can recreate some of the features of radiation-induced lung injury. Moreover, animal models of the condition do not typically recapitulate its complex presentation and entail serious ethical concerns.

Ethics 106
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Is machine learning the answer for long-acting injectable drugs?

European Pharmaceutical Review

Machine learning models used to guide the design of long-acting injectable drug formulations have been successfully tested by scientists at the University of Toronto. The research results signal the potential for machine to reduce reliance on trial-and-error testing, which slows the development of long-acting injectables (LAIs).

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Clinical Research 2.0 Must Embrace Change

PM360

In 2023, the Tufts Center for the Study of Drug Development, in collaboration with CluePoints and PwC, shared data from an industry- wide survey on RBQM adoption and attitudes. It ties together the concepts of quality by design (QbD) and RBQM to create a holistic, end-to-end clinical trial methodology. Now we need the people power.

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Evolving real-time dissolution prediction and product release

European Pharmaceutical Review

Researchers have developed a deterministic permeation model (DPM) that predicts the in vitro release profile of an active pharmaceutical ingredient (API) embedded in hydroxypropyl-methylcellulose (HPMC) matrix tablets. This requires RTRt to be developed. In their work, Horkovics-Kovats et al.

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Improving trial predictability: leveraging AI-powered analytics to guide trial design, strategy, and operations

pharmaphorum

AI-powered analytics, which leverage a wealth of real-world data, including electronic health records, claims data, public data sources, and disease registries can help sponsors proactively navigate ambiguities in trial design, fine tune study parameters, and evaluate scenarios to optimise design decisions and mitigate potential risks.