COVID-19：NEC、SARS-CoV-2遺伝子解析結果を公開：NEC OncoImmunity (NOI)（動画）：
COVID-19: NEC, SARS-CoV-2 gene analysis results released: NEC OncoImmunity (NOI)：
COVID-19：NEC，SARS-CoV-2基因分析结果发布：NEC肿瘤免疫（NOI）
COVID-19：NEC
日本電気：
AIを活用した新型コロナウイルス(SARS-CoV-2)の遺伝子解析の結果を公開した。
ワクチン開発を支援する取り組みとなる。
NEC/NEC OncoImmunity AS：
個別化がんワクチンの開発に用いているAI予測技術を適用し、SARS-CoV-2のゲノム配列を解析。
予測アルゴリズムを用いて全タンパク質を解析。
予測アルゴリズム：
エピトープ(ワクチンのターゲットとなり得る対象)を重複して含む「ホットスポット」を複数特定した。
- なお、世界中の多くの人に活用でき、
- かつ、ウイルスのタンパク質のなかで、
- 変異が少ないとされるものを、優先的に選定、
安全性を確保するため、人間のタンパク質と類似性が高いものや重要臓器に発現するものは除いたという。
PC Watch
https://www.google.co.jp/amp/s/pc.watch.impress.co.jp/docs/news/1249/063/amp.index.html
NEC publishes design blueprints for SARS-CoV-2 vaccines using its AI technology:
Tokyo, April 23, 2020 –
NEC Corporation (NEC; TSE: 6701) today announced analysis results from efforts using AI prediction platforms to design blueprints for SARS-CoV-2 vaccines
that can drive potent T-cell responses in the majority of the global population. This initiative by the scientific teams within the NEC Group to help combat outbreaks of COVID-19
and support international vaccine development efforts is led by NEC OncoImmunity (NOI) in collaboration with NEC Laboratories Europe (NLE).
These AI prediction platforms
are based on the AI technology used by NEC and NOI in the development of personalized neoantigen cancer vaccines.
During the analysis,
which is published at bioRxiv,
the team analyzed thousands of sequences from the SARS-CoV-2 virus (responsible for causing COVID-19)
and identified epitopes (potential vaccine targets) for the 100 most frequent HLA alleles (diverse immunological makeup) in the global population.
The prediction algorithm
scanned for epitopes across the entire repertoire of proteins in SARS-CoV-2, not only the spike surface protein that gives this family of coronavirus its name.
The team then used this data to identify “hotspots” in the viral proteome that contained overlapping and co-located epitopes from multiple HLA-alleles.
The optimal constellation of “hotspots”
was then selected by their algorithms to generate the optimal immune response with the broadest coverage of the human population,
whilst prioritizing hotspots that occurred in conserved regions of the viral proteome.
These conserved regions are less likely to mutate in future strains. In addition, hotspots containing viral epitopes that had significant similarity with human proteins,
especially those expressed in critical organs, were removed from the vaccine design blueprints to avoid adverse effects.
The analysis
demonstrates the significant capabilities of the NEC Group to leverage their AI platforms to design blueprints for a vaccine
that is safe and efficacious in a global population and could address the current and future divergent strains of the SARS-CoV-2 virus.
NEC is now publishing this research
to support scientific advancements in the field and is ready to start partnering efforts to pursue the development of an effective vaccine targeting the global population.
Press Releases | NEC