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Kandungan disediakan oleh Darshan Kulkarni. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Darshan Kulkarni atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
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๐Ÿ”’ Opportunities AI provides in Clinical Research

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Manage episode 456224004 series 3506216
Kandungan disediakan oleh Darshan Kulkarni. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Darshan Kulkarni atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

Subscriber-only episode

Today, we're discussing the FDA's use of artificial intelligence (AI) to transform clinical trials.

AI is emerging as a cornerstone in clinical research, with the FDA recognizing its potential in several key areas. First, predictive modeling allows AI to optimize pharmacokinetic profiles, streamlining dosing regimens and enhancing trial efficiency. Additionally, AI can create counterfactual simulations, enabling researchers to predict outcomes without putting real patients at risk.

AI also improves adherence through tools like smartphone alerts and electronic medication tracking, ensuring participants remain engaged. By automating administrative tasks and optimizing workflows, AI enhances operational efficiency, significantly reducing the time and costs associated with trial management.

Moreover, AI boosts participant recruitment and diversity by improving insight selection and engagement strategies, while AI-driven chatbots provide real-time support, predicting potential dropouts and improving retention. However, itโ€™s essential to implement proper training and safeguards to prevent overreliance on AI tools.

AI further aids in monitoring safety and predicting adverse events by detecting clusters of symptoms, allowing for timely interventions. Additionally, it streamlines the submission process by automating data analysis and report generation, ensuring compliance and speeding up approvals.

The integration of AI into clinical trials promises to make research more efficient, inclusive, and safe.

  continue reading

159 episod

Artwork
iconKongsi
 
Manage episode 456224004 series 3506216
Kandungan disediakan oleh Darshan Kulkarni. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh Darshan Kulkarni atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

Subscriber-only episode

Today, we're discussing the FDA's use of artificial intelligence (AI) to transform clinical trials.

AI is emerging as a cornerstone in clinical research, with the FDA recognizing its potential in several key areas. First, predictive modeling allows AI to optimize pharmacokinetic profiles, streamlining dosing regimens and enhancing trial efficiency. Additionally, AI can create counterfactual simulations, enabling researchers to predict outcomes without putting real patients at risk.

AI also improves adherence through tools like smartphone alerts and electronic medication tracking, ensuring participants remain engaged. By automating administrative tasks and optimizing workflows, AI enhances operational efficiency, significantly reducing the time and costs associated with trial management.

Moreover, AI boosts participant recruitment and diversity by improving insight selection and engagement strategies, while AI-driven chatbots provide real-time support, predicting potential dropouts and improving retention. However, itโ€™s essential to implement proper training and safeguards to prevent overreliance on AI tools.

AI further aids in monitoring safety and predicting adverse events by detecting clusters of symptoms, allowing for timely interventions. Additionally, it streamlines the submission process by automating data analysis and report generation, ensuring compliance and speeding up approvals.

The integration of AI into clinical trials promises to make research more efficient, inclusive, and safe.

  continue reading

159 episod

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