Quantum computing in Pharmaceutical Sciences

Quantum computing is emerging as a ground breaking technology with the potential to transform the pharmaceutical industry. Using quantum mechanical concepts like superposition and entanglement, QC is able to carry out intricate computations that are significantly more sophisticated than those that can be completed by traditional computers. Personalized medicine, molecular modeling, and drug development all benefit greatly from this capabilities. Traditional drug development is expensive and time-consuming, often requiring over a decade and significant financial investment. Quantum algorithms like the Variational Quantum Eigensolver and Quantum Phase Estimation facilitate precise calculations of molecular energies, significantly improving earlystage drug design and reducing experimental trial-and-error. When combined with quantum machine learning, it allows for the analysis of high-dimensional biomedical and genomic data, supporting the advancement of personalized medicine.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-02
DOI
https://doi.org/10.5281/zenodo.16726737
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum computing in Pharmaceutical Sciences

Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
article

Quantum computing in Pharmaceutical Sciences

article en

Abstract

Quantum computing is emerging as a ground breaking technology with the potential to transform the pharmaceutical industry. Using quantum mechanical concepts like superposition and entanglement, QC is able to carry out intricate computations that are significantly more sophisticated than those that can be completed by traditional computers. Personalized medicine, molecular modeling, and drug development all benefit greatly from this capabilities. Traditional drug development is expensive and time-consuming, often requiring over a decade and significant financial investment. Quantum algorithms like the Variational Quantum Eigensolver and Quantum Phase Estimation facilitate precise calculations of molecular energies, significantly improving earlystage drug design and reducing experimental trial-and-error. When combined with quantum machine learning, it allows for the analysis of high-dimensional biomedical and genomic data, supporting the advancement of personalized medicine.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 75%
Quantum Computing Algorithms and Architecture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantum computing in Pharmaceutical Sciences · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS