Dominika Wilczok’s research while affiliated with Duke University and other places

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Publications (3)


Figure 1. The layered structure of machine learning, deep learning, and generative artificial intelligence in the context of aging research. ML encompasses foundational methods, including linear regression and support vector machines, for biomarker identification and biological age prediction. DL builds on ML, employing architectures such as convolutional and recurrent neural networks to analyze complex, multimodal datasets. GenAI extends DL capabilities through generative models, including GANs and transformers, enabling synthetic data generation, multimodal biomarker creation, and advanced applications in drug discovery and aging-related interventions.
Figure 2. A timeline of major milestones in AI applications for aging research from 2014 to 2024.
Figure 3. Diverse applications of GenAI across aging research.
Deep aging clocks based on deep neural networks.
Deep learning and generative artificial intelligence in aging research and healthy longevity medicine
  • Literature Review
  • Full-text available

January 2025

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124 Reads

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2 Citations

Aging

Dominika Wilczok

With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep aging clock development, geroprotector identification and generation of dual-purpose therapeutics targeting aging and disease. The paper explores the emergence of multimodal, multitasking research systems highlighting promising future directions for GenAI in human and animal aging research, as well as clinical application in healthy longevity medicine.

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Progress, Pitfalls, and Impact of AI-Driven Clinical Trials

December 2024

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9 Reads

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2 Citations

Since the deep learning revolution of the early 2010s, significant efforts and billions of dollars have been invested in applying artificial intelligence (AI) to drug discovery and development (AIDD). However, despite high expectations, few AI‐discovered or AI‐designed drugs have entered human clinical trials, and none have achieved clinical approval. In this perspective, we examine the challenges impeding progress and highlight opportunities to harness AI's potential in transforming drug discovery and development.


Figure 1. Timeline of longevity biotechnology. Key breakthroughs in the AI, biomarkers and clocks, geroscience, and clinical trials and applications in ageing and longevity fields since 2013.
Figure 3. Integration of AI, biomarkers and clocks, geroscience, and longevity medicine in advancing human healthspan.
Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity

October 2024

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768 Reads

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13 Citations

Aging

Yu-Xuan Lyu

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Qiang Fu

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Dominika Wilczok

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[...]

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Daniela Bakula

The recent unprecedented progress in ageing research and drug discovery brings together fundamental research and clinical applications to advance the goal of promoting healthy longevity in the human population. We, from the gathering at the Aging Research and Drug Discovery Meeting in 2023, summarised the latest developments in healthspan biotechnology, with a particular emphasis on artificial intelligence (AI), biomarkers and clocks, geroscience, and clinical trials and interventions for healthy longevity. Moreover, we provide an overview of academic research and the biotech industry focused on targeting ageing as the root of age-related diseases to combat multimorbidity and extend healthspan. We propose that the integration of generative AI, cutting-edge biological technology, and longevity medicine is essential for extending the productive and healthy human lifespan.

Citations (2)


... Quantum algorithms, such as the quantum approximate optimization algorithm, demonstrate the potential to outperform classical methods in solving complex optimization problems. This could revolutionize our understanding of aging mechanisms and pave the way for innovative therapeutic strategies [47]. April 21, 2025 Volume 31 Issue 15 ...

Reference:

Delaying liver aging: Analysis of structural and functional alterations
Deep learning and generative artificial intelligence in aging research and healthy longevity medicine

Aging

... Longevity is the most general and integrative parameter for evaluating the therapeutic effects of any interventions (Lyu et al. 2024). Another integrative parameter directly related to life expectancy is biological age. ...

Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity

Aging