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医療現場を支えるHOCITGROUPのAI画像診断支援ソリューション
AI画像診断支援ソリューションを用いて、CT画像等の膨大な医療画像を自動的に診断し異常を検知。
放射線科医の負担軽減に寄与。
医療・ヘルスケア | AI（人工知能）2020年2月14日

ビールの「濾過計画業務」を
デジタル活用で1/6に効率化
1日最大6.5時間を必要としていた熟練者による業務が最短55分に短縮
製造 | AI（人工知能）2020年2月7日

三井住友海上あいおい生命様
接客の第一印象をAIが評価
効果的なセルフトレーニングでお客さま対応品質の向上につなげる
金融 | AI（人工知能）2019年10月17日

ゲッティイメージズ ジャパン株式会社様
ゲッティイメージズとAIが選ぶ「今年の1枚」を発表
AI（人工知能）2019年5月21日

日産自動車様
LINE×AIチャットボットによるスマホからの試乗予約が自動車業界の常識を変え、未来のクルマ選びをも変革する
個人のお客様向け | 製造 | AI（人工知能） | ロボティクス2019年1月28日

イーレックス様
データの集約で予実管理の精度が大幅にアップ
各種業務効率の向上に加えて経営判断の迅速化も実現
電力・ガス・水道2018年12月10日

東京海上日動火災保険様
世界8カ国、海外の関係者を巻き込んだ、外航貨物保険における保険金請求へのブロックチェーン技術適用に関する実証実験に成功！
金融 | ブロックチェーン2018年11月22日

ブロックチェーンコンソーシアム参加企業18社
ブロックチェーン技術を活用した貿易情報連携基盤の実現
ブロックチェーン2018年11月1日

大手クレジットカード会社等
法人（加盟店）審査ソリューション
2018年11月1日

国内7割の銀行
オープンAPIを実現するSoE基盤「OpenCanvas」の提供
2018年11月1日

城北信用金庫様、多摩信用金庫様等
信用金庫業界向けアプリバンキングの構築による顧客接点拡大
2018年11月1日

西日本シティ銀行様、北越銀行様等
次世代型バンキングアプリ「My Pallete」の導入
2018年11月1日

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行业服务出版年份查看所有

 

HOCIT GROUP的AI图像诊断支持解决方案支持医学实践
AI图像诊断支持解决方案用于自动诊断巨大的医学图像（例如CT图像）并检测异常。
帮助减轻放射科医生的负担。
医疗/卫生保健| AI（人工智能）2020年2月14日

啤酒“过滤计划事业”
使用数字将效率提高到1/6
每天最多需要6.5个小时的技术工人所需的时间被缩短到最短的55分钟。
制造业| AI（人工智能）2020年2月7日

三井住友青井生命
人工智能评估客户服务的第一印象
有效的自我培训有助于提高客户响应质量
金融| AI（人工智能）十月17，2019

日本盖蒂图片社
盖蒂图片社和AI选择“年度最佳”
AI（Artificial Intelligence）2019年5月21日

日产汽车
使用LINE x AI chatbot从智能手机预订试驾将改变汽车行业的常识并改变未来的汽车选择
对于个人客户|制造业| AI（人工智能）|机器人技术2019年1月28日

埃莱克斯
数据聚合大大提高了实际管理的准确性
除了提高运营效率，还可以加快管理决策
电力，天然气，水2018年12月10日

东京海上和日道消防保险
成功地进行了涉及8个国家和海外利益相关方的区块链技术应用于海洋货运保险索赔的演示性实验！
金融|区块链2018年11月22日

参加区块链财团的18家公司
利用区块链技术实现贸易信息协作平台
Blockchain 2018年11月1日

主要信用卡公司等
企业（会员店）考试解决方案
2018年11月1日

70％的国内银行
提供实现开放API的SoE平台“ Open Canvas”
2018年11月1日

Johoku Shinkin银行，Tama Shinkin银行等
通过为Shinkin Bank行业构建应用程序银行来扩大客户联系
2018年11月1日

西日本城市银行，北越银行等
下一代银行应用程序“ My Pallete”的介绍
2018年11月1日

Okyakusama jirei o toiawase gyōshu sābisu keisai-nen subete o miru iryō genba o sasaeru HOCITGROUP no AI gazōshinda shien soryūshon AI gazōshinda shien soryūshon o mochiite, CT gazō-tō no bōdaina iryō gazō o jidōtekini shindan shi ijō o kenchi. Hōshasenkai no futan keigen ni kiyo. Iryō herusukea | AI (jinkō chinō) 2020-nen 2 tsuki 14-nichi bīru no `roka keikaku gyōmu' o dejitaru katsuyō de 1/ 6 ni kōritsu-ka 1-nichi saidai 6. 5-Jikan o hitsuyō to shite ita jukurenmono ni yoru gyōmu ga saitan 55-bu ni tanshuku seizō | AI (jinkō chinō) 2020-nen 2 tsuki 7-nichi mitsuisumitomokaijō ai oi seimei-sama sekkyaku no daiichiinshō o AI ga hyōka kōkatekina serufutorēningu de okyaku-sama taiō hinshitsu no kōjō ni tsunageru kin'yū | AI (jinkō chinō) 2019-nen 10 tsuki 17-nichi gettiimējizu Japan kabushikigaisha-sama gettiimējizu to AI ga erabu `kotoshi no 1-mai' o happyō AI (jinkō chinō) 2019-nen 5 tsuki 21-nichi Nissanjidōsha-sama LINE×AI chattobotto ni yoru sumaho kara no shijō yoyaku ga jidōsha gyōkai no jōshiki o kae, mirai no kuruma erabi o mo henkaku suru kojin no okyakusama-muke | seizō | AI (jinkō chinō) | robotikusu 2019-nen 1 tsuki 28-nichi īrekkusu-sama dēta no shūyaku de yojitsu kanri no seido ga ōhaba ni appu kakushu gyōmu kōritsu no kōjō ni kuwaete keiei handan no jinsoku-ka mo jitsugen denryoku gasu suidō 2018-nen 12 tsuki 10-nichi tōkyōkaijōnichidōkasaihoken-sama sekai 8-kakoku, kaigai no kankei-sha o makikonda,-gai kō kamotsu hoken ni okeru hokenkinseikyū e no burokkuchēn gijutsu tekiyō ni kansuru jisshō jikken ni seikō! Kin'yū | burokkuchēn 2018-nen 11 tsuki 22-nichi burokkuchēnkonsōshiamu sanka kigyō 18-sha burokkuchēn gijutsu o katsuyō shita bōeki jōhō renkei kiban no jitsugen burokkuchēn 2018-nen 11 tsuki 1-nichi ōte kurejittokādo kaisha-tō hōjin (kamei-ten) shinsa soryūshon 2018-nen 11 tsuki 1-nichi kokunai 7-wari no ginkō ōpun api o jitsugen suru SoE kiban `OpenCanvas' no teikyō 2018-nen 11 tsuki 1-nichi Jōhoku shin'yōkinko-sama, Tama shin'yōkinko-sama-tō shin'yōkinko gyōkai-muke apuribankingu no kōchiku ni yoru kokyaku setten kakudai 2018-nen 11 tsuki 1-nichi nishinihonshitiginkō-sama, Hokuetsuginkō-sama-tō jisedai-gata bankinguapuri `My Pallete' no dōnyū 2018-nen 11 tsuki 1-nichi 1 2 3 4 5

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HOCIT GROUP's AI image diagnosis support solution supporting medical practice
An AI image diagnosis support solution is used to automatically diagnose huge medical images such as CT images and detect abnormalities.
Helps reduce the burden on radiologists.
Medical/Healthcare | AI (Artificial Intelligence) February 14, 2020

Beer "filtration planning business"
Use digital to increase efficiency to 1/6
The time required for skilled workers who required up to 6.5 hours a day was reduced to 55 minutes at the shortest.
Manufacturing | AI (Artificial Intelligence) February 7, 2020

Mitsui Sumitomo Aioi Life
AI evaluates first impression of customer service
Effective self-training helps improve customer response quality
Finance | AI (Artificial Intelligence) October 17, 2019

Getty Images Japan Co., Ltd.
Getty Images and AI Choose "One of the Year"
AI (Artificial Intelligence) May 21, 2019

Nissan Motor
Booking a test drive from a smartphone with the LINE x AI chatbot will change the common sense of the automobile industry and transform the choice of future cars
For Individual Customers | Manufacturing | AI (Artificial Intelligence) | Robotics January 28, 2019

Elex
The accuracy of the actual management is greatly improved by the data aggregation
In addition to improving operational efficiency, speed up management decisions
Electricity, gas, water December 10, 2018

Tokio Marine & Nichido Fire Insurance
Succeeded in a field trial of applying blockchain technology to insurance claims in ocean freight insurance involving stakeholders from 8 countries and overseas!
Finance | Blockchain November 22, 2018

18 companies participating in the blockchain consortium
Realization of a trade information collaboration platform utilizing blockchain technology
Blockchain November 1, 2018

Major credit card companies, etc.
Corporate (Member Store) Examination Solution
November 1, 2018

70% of domestic banks
Provision of SoE platform "Open Canvas" that realizes open API
November 1, 2018

Johoku Shinkin Bank, Tama Shinkin Bank, etc.
Expand customer contacts by building application banking for the Shinkin Bank industry
November 1, 2018

West Japan City Bank, Hokuetsu Bank, etc.
Introduction of next-generation banking application "My Pallete"
November 1, 2018

AI Technology enhances shopping experiences to create the new future.

私達は 流通業界を変えるために存在しています。

 

流通業界は、データの利活用は実は未だ不十分であり、
非効率な部分が多く存在している業界です。

私たちは、IoTデバイスを用いてリアルのオフラインデータを収集し、
データおよびAI技術活用したソリューションを提供することで
流通産業の最適化など改善を実現することを目指しています。

ショッパーに対するOne to Oneマーケティング、
商品管理の最適化を目的とするカテゴリーマネジメント、
製造から小売までの非効率を改善するサプライチェーンマネジメントなどに取り組んでおり、
これらのソリューションを多くの実店舗に導入していることが私たちの強みです。

私たちは流通産業のAI化を通して、「流通のムリ・ムダ・ムラ」を取り除き、
流通の構造改革を進めていきます。

リテールの発展による新しい買い物体験を実現する未来と
更なる豊かさを社会を目指して行きます。

事業内容（プロダクト）

AIのビジネス実装には データの集積が欠かせません。
わたしたちのリテールAIプラットフォームは、 データの収集から分析、
ソリューション導入、最適化までを 一気通貫で担います。

店舗に様々なIoTデバイスを設置し、
これまで捉えることのできなかった 情報を収集します。

 

AIカメラ

AIカメラは、売場状態と、ショッパーの棚前行動を収集します。売場の鮮度感を保つためには、定期的なメンテナンスが必要ですが、反面、作業コストが膨大になります。リテールAIカメラは、棚割設計や発注コントロール、補充作業の簡略化、およびタイミングの最適化などを支援するデータを収集し、売場の最適化に寄与します。

 

スマートレジカート

ショッパーの店頭でのショッピングシーンに寄り添い、 レジ待ちを軽減させるなど、リアル店舗における買い物時のストレスを解消します。さらに、ショッパーの購入状況に応じたオススメ商品やクーポンの提示を行い、ショッピングの楽しさを加速させます。また、これまでデータ化されていなかった、購入プロセス・データも収集します。

Apps

IoTデバイスで収集した情報を、 「見える化・予測・制御」分野に活用

単なる売場改善にとどまらず、 サプライチェーンや、マーケティング分野まで
活用を広げ、ビジネスアクションに つなげます。

Media

店頭メディアサービスを中心に、 購入の意思決定を行う最終局面での、
効果的なセールスプロモーションを実現します。AIカメラ・スマートレジカート・サイネージ・店内放送など様々な店内メディアとモバイルアプリなどの店外メディアを活用し、カスタマージャーニーの要所におけるセールスプロモーションを実現します。

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Welcome to the entrance to the world of acupuncture
Acupuncturist: a profession that will not disappear in the AI ​​era
With the development of AI (artificial intelligence), many existing occupations are expected to disappear. It is said that artificial intelligence has gradually entered the high-level intellectual professional fields such as finance and legal affairs, and has begun to serve people.

But what about acupuncture?

Acupuncture is a delicate and special technique that cannot be easily replaced by computers or machines. It can only be done manually. We often hear about their physical conditions from patients, consider the cause of the current symptoms, and select appropriate treatment points from 361 acupoints (acupoints) for acupuncture. This is a complex and delicate technique. It is impossible for robots. Even if it is possible, it will not be controlled by practitioners.

On the contrary, since it is surrounded by digital devices every day, do you think it needs the warmth, softness and safety of human hands? Acupuncture is a technology that is expected to become more valuable in the future AI era.

The WHO (World Health Organization) has also certified the therapeutic effects of acupuncture. Acupuncture therapy is good at treating symptoms that are difficult to improve by Western medicine, pain that has not been diagnosed as "discomfort" (discomfort) according to the examination results, and pain that cannot be completely cured. It is understandable that in recent years, the upsurge of Oriental medicine is coming, and it is said that this is a very stressful society. There is a growing demand for acupuncturists who can understand and treat patients' pain.

In addition, acupuncturists are long-term participants of men and women. This is not hard work, so even after aging, you can use the skills and intuition accumulated according to your physical strength to stand in the field of treatment. This is a lifelong job, you can improve your skills while you work, and cultivate opportunities for success while reaping rewards.
 

ACCELERATE OUTCOMES WITH A BACKBONE FOR ARTIFICIAL INTELLIGENCE.

makes machine learning operational by connecting models to the real-world decisions they inform. Often, AI/ML algorithms live in experimental vacuums. Foundry provides the end-to-end infrastructure an organization needs to apply AI/ML to real problems and real data:

  • A data foundation.  provides the data engineering capabilities an organization needs to deploy AI/ML models it can trust. Organizations use  to build a solid foundation of sufficient, quality data, then bring that data into daily operations.

  • Production deployment infrastructure. revolutionizes the way organizations build and deploy AI/ML by combining a data foundation with end-to-end algorithm deployment infrastructure. Data scientists and engineers can customize, deploy, assess, and compare across homegrown, open-source, and third-party algorithms. All models are tightly integrated with end-to-end platform capabilities, ranging from feature curation and health checks to model management to inference/serving to outcome monitoring.

  • Faster feedback loops. AI/ML models rarely work on a "set it and forget it" basis.  integrates the full model lifecycle with end user actions and feedback, and with operational decisions and outcomes. This enables operationally oriented model monitoring, management, understanding, selection, and adjustment. The result is more adaptable and ambitious AI/ML, faster.

UNITE THE ORGANIZATION AROUND A SHARED ENVIRONMENT FOR MACHINE LEARNING.

The most effective AI/ML encodes and supercharges an organization's unique expertise. That requires uniting an organization's data scientists, decision-makers, and everyday employees in an environment for collaborating on AI/ML-powered operations.  collaboration infrastructure drives AI/ML that brings the organization together:

  • A unifying ontology. ontology translates an organization's complex data landscape into human-readable concepts. built models reflect how an organization views the world and unite data scientists, engineers, analysts, executives, and operational end users around a common semantic layer.

  • Granular security controls. lets organizations define granular access control policies at the integration stage, then propagates those policies intelligently across the system. Organizations can promote collaboration confidently with granular data security and transparent data governance.

  • Model templates.model templates empower low-code and no-code AI/ML so even non-technical users can use AI to accelerate and enrich their workflows.

MAXIMIZE IMPACT AND MINIMIZE RISK WITH A PLATFORM DESIGNED FOR RESPONSIBLE ENGINEERING.

Our approach to AI/ML in  reflects our foundational belief in augmenting human intelligence, not replacing it. We believe AI/ML algorithms are most effective when they empower humans to ask complex questions, interpret answers, and act on results. At public and private sector organizations around the world, driven AI/ML is accelerating human decision-making by:

  • Surfacing new leads in dark web, weapons trafficking, financial fraud, and drug trafficking investigations so investigators can identify persons of interest more quickly

  • Aggregating and correlating biomedical research data to streamline drug discovery

  • Processing entity resolution suggestions so analysts can focus on making assessments rather than manually sorting and tagging data

  • Analyzing massive-scale sensor data so that engineers can make better aircraft maintenance decisions

  • Rapidly generating simulations while allowing operators to tweak scenario variables, leading to better-informed decisions optimized for different variables (e.g., safety rating and production quantity)

I see our approach to ethical machine learning as being grounded in an appreciation for both the promise and limitations of human-computer collaboration. The promise of AI is in augmenting and enhancing human intelligence, expertise and experience. Think helping a aircraft mechanic make better, more accurate and more timely repairs – not automating the mechanic out of the picture.

— Anthony Bak, Co-Lead of Palantir's Machine Learning team, in an interview with CTOVision

Protecting privacy and preserving civil liberties is fundamental to our mission.ships with technical capabilities that enable ethical engineering and ethical machine learning, including data protection features such as granular access controls, data provenance and lineage tracking, data retention and deletion management, and audit logging.  also enables industry-leading monitoring and validation for AI models. Its flexible, configurable tools let organizations evaluate model bias, in terms of both the data used to train the model and model outcomes.

We recognize that technology alone can't fully mitigate the risks of machine bias. Our dedicated Privacy and Civil Liberties team works with our engineers and our customers to approach building and deploying AI/ML thoughtfully.

Acupuncture significantly reduces AI-associated arthralgias

Publish date: December 8, 2017

By 

Roxanne Nelson

 

 

 

REPORTING FROM SABCS 2017

SAN ANTONIO – Acupuncture significantly reduced joint pain that was associated with the use of aromatase inhibitors (AIs) in women with early breast cancer, according to new findings reported at the San Antonio Breast Cancer Symposium.

The randomized, phase 3 SWOG S1200 clinical trial found that, compared with sham acupuncture and a control group receiving no therapy, women receiving acupuncture reported significantly lower scores on the Brief Pain Inventory–Short Form (BPI).

“We have shown consistently, with multiple measures assessing pain and stiffness, that true acupuncture generated better outcomes than either control group in a large multicenter trial,” said lead author Dawn L. Hershman, MD, leader of the Breast Cancer Program at the Herbert Irving Comprehensive Cancer Center at NewYork-Presbyterian/Columbia University Medical Center. “Acupuncture provides a nonpharmacologic option that can improve symptoms and possibly increase AI adherence and subsequent breast cancer outcomes.”

AIs can reduce both early breast cancer recurrence and mortality. Dr. Hershman noted that these agents are effective in the adjuvant setting and for prevention “but we know that it doesn’t work if you don’t take it. Noncompliance is a major problem among women taking hormonal therapy.”

Noncompliance is multifactorial and one of the main reasons women discontinue their therapy early is because of arthralgias or joint discomfort. “We were interested in a nonpharmacologic intervention, to assess whether or not we could control these symptoms.”

Dr. Hershman pointed out acupuncture provides a safe and effective alternative for patients reluctant to take a prescription medication that can result in other side effects. “Identification of nonopioid options for pain control is a public health priority,” she said.

Acupuncture is a popular nonpharmacologic modality and widely used for a number of indications. Several single-institution studies have suggested that it may be useful for controlling AI-associated arthralgias, while other studies have not demonstrated a benefit.

In this trial, the authors evaluated the efficacy of acupuncture, compared with sham acupuncture or waitlist control, in the treatment of AI associated arthralgia in a large population of patients. The study was conducted at 11 centers.

The cohort comprised 226 postmenopausal women diagnosed with early-stage, hormone receptor–positive breast cancer who were receiving treatment with AIs. The primary endpoint was the decline in joint pain as measured by BPI-SF at 6 weeks, and to assess the duration of the effect, the women were followed for an additional 12 weeks.

Within this group, 110 were randomized to true acupuncture; 59 to sham acupuncture, and 57 to waitlist control (no treatment). Patients receiving true or sham acupuncture had sessions three times a week for 6 weeks followed by one session per week for 6 more weeks. Pain status was reported at baseline, during treatment, and then afterwards, using a variety of measurement tools including the BPI-SF, which is a self-administered 14-item questionnaire that evaluates pain severity on a 0-10 scale, and the impact of pain on activities of daily living.

At 6 weeks, the true acupuncture treatment arm reported significantly lower BPI worst pain scores than those in the sham acupuncture and the waitlist control arms. The mean BPI worst pain for the true acupuncture arm was 0.92 points lower than the sham acupuncture arm (P = .01) and 0.96 points lower than the waitlist control arm (P = .01). The proportion of patients experiencing a large reduction in BPI worst pain (greater than 2) was significantly greater in the true acupuncture arm, compared with the other groups: 58% versus 33% percent and 31%, respectively. The differences continued to remain statistically significant at 24 weeks, even though the treatment only continued for 12 weeks.

Associated adverse effects were minimal with true and sham acupuncture and limited to grade 1 bruising.

The cost of the 12-week intervention was about $1,250 or $65-$75 a session. “We feel that there is now sufficient evidence to support insurance coverage of acupuncture of AI arthralgia.”

In a discussion of the paper, Dr. Anne Partridge, from the Dana Farber Cancer Center, noted that it is imperative to seek new ways to improve outcomes in breast cancer, and AIs are contributing to that. However, she echoed the concern that nonadherence to treatment is a “tremendous problem” and hampers the clinical effectiveness of AI therapy.

The rate of discontinuation during the first year of therapy is 20% within the first year and up to 40% of patients do not take them daily. Both early discontinuation and nonadherence contribute to mortality.

Based on these results from the largest randomized controlled trial looking at acupuncture in this setting, should physicians be recommending acupuncture to patients prescribed AI therapy?

“The short answer is, why not?” said Dr. Partridge, “And that we should be recommending it for some of our patients.”

However, there are a number of issues that need to be addressed, she added. The duration of treatment is not known, and the need for follow-up treatment or the frequency of it is not known. The generalizability of it is also unclear when looking at a larger population, and acupuncture is highly operator dependent.

“There are cost and access issues, and insurance right now offers very limited coverage,” she said.

Importantly, Dr. Partridge emphasized, “We know that it will help symptoms, but will it improve adherence to AI?”

It may improve adherence for some patients, but “side effects are only one factor,” she said. “Adherence behavior is complicated. We need to figure out how to optimize these therapies in our patients.”

This study was supported by the National Institutes of Health National Center for Complementary and Integrative Health and the Office of Research on Women’s Health, and grants from the NIH/National Cancer Institute Division of Cancer Prevention. Dr. Hershman declared no conflicts of interest. Dr. Partridge had no disclosures.

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Illumina, Chinese Children's Hospital to Launch Newborn Sequencing Study

Apr 23, 2019

 

| 

staff reporter

 

NEW YORK (GenomeWeb) – Illumina and the Children's Hospital of Fudan University in China plan to launch a study of whole-genome sequencing in the hospital's neonatal intensive care unit to determine whether it can be used as a diagnostic for critically ill infants, Illumina said this week.

According to Illumina, the researchers plan to enroll 200 patients and compare the diagnostic rate of rapid WGS with genetic diagnostic methods such as microarray analysis and gene panel sequencing.

The researchers will also compare the time it takes to reach a diagnosis, impact on the patient's prognosis, and turnaround time.

Illumina will provide the sequencing reagents and the Children's Hospital of Fudan University will conduct the testing and data analysis and also be responsible for reporting results and providing genetic consultations with family members.

The hospital is also a sponsor of the Newborn Genome Project, which is creating a genome database for newborns in China in order to develop better methods for detecting genetic diseases in newborns and to establish standards for neonatal genetic diseases.

UK Study Details Liquid Biopsy's Ability to Guide Metastatic Breast Cancer Treatment

Dec 13, 2019

 

| 

staff reporter

 

NEW YORK – Researchers from the Institute of Cancer Research, London and the Royal Marsden NHS Foundation Trust have presented data demonstrating that blood-based genotyping assays can accurately detect specific biomarkers and potentially be used to guide targeted treatment of metastatic breast cancer. 

The researchers used Guardant Health's liquid biopsy assay and Bio-Rad Technologies' droplet digital PCR (ddPCR) testing to identify errors — including mutations in the HER2, ESR1 and AKT1 genes — in circulating tumor DNA (ctDNA) that had been shed into the patients' bloodstream. 

During a presentation this week at the San Antonio Breast Cancer Symposium (SABCS), Nicholas Turner, molecular oncology professor at the Institute of Cancer Research, explained that his team wanted to solve the issue of genotyping breast cancer tumors without having to perform multiple biopsies. Turner highlighted the need for prospective studies to assess the accuracy of ctDNA testing in routine practice and the potential of these tools to guide targeted therapy without requiring solid tissue testing. 

With funding from Stand Up To Cancer (a fundraising campaign from Cancer Research UK and Channel 4) Turner's team therefore launched an ongoing prospective study, called "plasmaMATCH," to examine the clinical utility of ctDNA for metastatic breast cancer detection. The group enrolled a total of 1,044 patients with advanced breast cancer who had either progressed on prior drug therapy or relapsed within a year after adjuvant chemotherapy. 

The researchers analyzed ctDNA in blood samples from patients using the Guardant360 sequencing-based assay and Bio-Rad's ddPCR as an orthogonal method. Patients with identified mutations could also enroll in a treatment arm of the study that matched their mutation. 

Turner and his team split the patient population into three major cohorts depending on specific genetic errors found in ctDNA: ESR1 mutations, HER2 mutations, and AKT-1 mutations in estrogen-receptor-positive breast cancer. The researchers also added a fourth cohort that had AKT-1 and PTEN mutations based on both ctDNA and tumor sequencing results, as well as a fifth group with triple-negative breast cancer without mutations. 

While Turner's team's initially aimed to measure the response rate of targeted therapies matched to mutations in ctDNA without tissue testing, the researchers also monitored the frequency of mutations, accuracy of testing, proportion of patients entering a treatment cohort, and the activity in clonality-dominant versus subclonal mutations. Turner's team discovered that 784 patients who had cfDNA testing done with both Guardant360 and ddPCR had "very strong agreement" of between 96 and 99 percent. Comparing the ctDNA to the patients' tumor samples to validate the plasmaMATCH findings, the researchers found that the liquid biopsy assay had an overall sensitivity of 93 percent. 

Guardant360 also identified several more targetable alterations than hotspot testing, including over 35 percent more PIK3CA mutations that can be targeted by US Food and Drug Administration-approved therapies. The assay also detected significantly more ESR1 mutations and found previously undetected microsatellite instability and ERBB2 mutations.   

The researchers provided 142 patients that had specific identified mutations experimental targeted therapies as part of the study, and they plan to test the treatments that showed initial promise in larger clinical trials. 

The researchers now believe that they can use blood testing to identify rare subtypes of breast cancer, in addition to potentially replacing more invasive methods of breast cancer detection. 

"We have now confirmed that blood tests can quickly give us a bigger picture of the mutations [that] are present within multiple tumors throughout the study," Turner said in a statement.  

"We show that circulating tumor DNA testing offers a simple, efficient, and fast method of tumor genotyping," Turner also noted during the presentation at SABCS. "The patients with mutations identified in their ctDNA have efficacy with matching target[ed] therapies." 

The researchers believe the blood-based assays are now reliable enough to be applied routinely by clinicians after receiving regulatory approval.

"As the number of treatment-relevant genomic alterations in metastatic breast cancer continues to grow, it is critical that oncologists have a simple and reliable way to comprehensively test for this information about their patients," Guardant Health Global Chief Medical Officer Rick Lanman said in a statement. "Guardant360 detected changes in the genome picture over time … and also identifies targetable but uncommon genomic biomarkers."

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