Evaluating the approach on other ADMET endpoints and datasets

The gap

Evidence profile

Sourced from the future-work section and synthesized and abstract of the source papers, classified as general, spanning 4 journals.

Supporting evidence — 5 representative gaps

• ADMET Property Prediction with Quantum-Inspired Preprocessing (2026) · bioRxiv · doi

  Evaluating the approach on other ADMET endpoints and datasets. Investigating the effect of the thresholds on circuit size and model performance. Exploring the application of quantum-inspired methods to other machine learning tasks in drug discovery.

  generalfuture-work sectionevidence 5/5
  Keywords: evaluating approach other admet endpoints datasets investigating effect
• Quantum Computing : Fundamental Principles, Quantum Algorithms, and Emerging Applications (2026) · International Journal of Advanced Research in Science Communication and Technology · doi

  None of these studies evaluate quantum machine learning methods for molecular property prediction (QSAR/ADMET) on public drug-discovery datasets with explicit comparison to classical baselines and noise-robustness analysis on NISQ hardware. Existing work discusses quantum algorithms in principle but does not benchmark variational quantum circuits or quantum kernels against standard molecular fingerprints on real molecular datasets with measured generalization and uncertainty quantification.

  generalsynthesizedevidence 5/5
  Keywords: none studies evaluate quantum machine learning methods molecular
• Quantum Computing : Fundamental Principles, Quantum Algorithms, and Emerging Applications (2026) · International Journal of Advanced Research in Science Communication and Technology · doi

  No paper in this collection reports a reproducible, open-source implementation of a quantum machine learning model for any drug-discovery or genomics task with publicly available code, trained model, and benchmark results—limiting practical adoption and verification for the researcher's 2-day implementation timeline.

  generalsynthesizedevidence 5/5
  Keywords: paper collection reports reproducible open-source implementation quantum machine
• Quantum Kernel Regression and Variational Quantum Regression for the CCS Prediction of Dissolved Organic Matter: A Comparative Benchmarking Study (2026) · Journal of the American Society for Mass Spectrometry · doi

  Abstract Recent advances in quantum machine learning (QML) offer new opportunities for chemical property prediction, yet their practical performance relative to established classical models remains poorly characterized on real-world datasets.

  generalabstractevidence 5/5
  Keywords: abstract recent advances quantum machine learning offer opportunities chemical property prediction practical performance relative established
• Hybrid Quantum-Classical Neural Architecture Search (2026) · arXiv

  Further research is needed to explore the application of the proposed methodology to various quantum machine learning tasks. The incorporation of additional objectives, such as energy consumption, could be explored. The development of more efficient algorithms for searching the quantum circuit configuration space is an area for future research.

  generalfuture-work sectionevidence 4/5
  Keywords: further research needed explore application proposed methodology various

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