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以数据为中心的软件解决方案如何影响分析化学实验室?
行业洞察力

以数据为中心的软件解决方案如何影响分析化学实验室?

以数据为中心的软件解决方案如何影响分析化学实验室?
行业洞察力

以数据为中心的软件解决方案如何影响分析化学实验室?

学分:Pixabay。
I would say many of our customers have some type of siloed solution in place now and they’ve invested into that, so they may not move quickly. They may do some type of adjacent development which Agilent can help them with. Those siloes tend to look like a Chromatography Data System (CDS), a Laboratory Information Management System (LIMS), and then sometimes a lab execution system which can often be an Electronic Laboratory Notebook (ELN) or similar. Agilent’s vision is to offer labs that are starting out, a data system that combines a lot of these functions together - for example a LIMS and an ELN that interfaces directly with the CDS. Agilent acquired a company in May 2018 called Genohm which offers a solution to digitize your lab workflow, combining LIMS with an ELN - called SLIMS, for simple LIMS. Our plan is to integrate that directly with our CDS over the next 12 to 18 months.

Q: With the cloud, how do you ensure that you meet the needs of the different labs that you serve?


A:
Agilent did an extensive market survey and we believe segmented the market accurately to offer a variety of different types of cloud solutions. Here are some examples. First, there is the larger customer moving their whole CDS to the cloud - we have done that. The second is using the cloud just as storage.

Ultimately, a future scenario for those smaller and medium-sized labs would be a Software-as-a-Service (SaaS) solution. For example, an Agilent GC could be plugged into the network, perhaps by scanning a barcode which would auto connect to the data system and the storage in the cloud. Agilent could assist with that. We think that is especially appealing to the smaller and medium-sized labs because it greatly reduces their IT spend and gets them up and running quickly.

Q: For a lot of people a lab will do something a particular way because they have always done it that way. How do you address the challenge of getting people to embrace change and adopt new systems?


A:
It has become a lot easier because of the consumer market. A young lab technician perhaps straight out of college starting out in an analytical lab, may have never installed software on a workstation. It is interesting, we are not driving this, our customers are.

Q: Are you surprised by the speed of the change?


A:
Yes! What has become apparent is that our customers’ perspective has shifted from “cloud or no cloud?”, to “absolutely cloud and absolutely using these enterprise architectures that Amazon and Google etc. have provided”. We are also seeing some of our customers willing to share their data with us. This enables us to say to them “our algorithm looked at your last 20 runs and we noticed there is some decrease in performance”, or “it looks like you are doing a glycan separation, did you know that if you use these techniques you would get a better result?” We can help them analytically and that builds trust, so long as the proper security safeguards are in place.

Q: Are you currently able to use information on usage to look for trends, if there are common breakdowns or glitches that are occurring for example, so that you can focus future developments and refinements?


A:
Yes. We offer this now. There is an opt-in capability that allows customers to provide us access to their aggregated service data and performance data, enabling us to go back to them and say for example, “you have three main applications, and your biggest application is only using 40% of your resources and is starved of capacity, but your other two applications are not, so have you considered switching some of those resources to your biggest application?” This service is readily available, we have seen adoption where a lab has 300 GC’s, 300 LC’s, for them that solution is very beneficial. In the future, it could potentially all be automated.

Q: Many people out there do software. What do you think really sets you aside or is there anything that you would say is unique or better?


A:
Agilent takes customer success extremely seriously. We want to make sure the customer gets it right. That is a philosophy across the company, truly in the culture, and I think comes from the Hewlett Packard days. So that is one thing that sets us aside from our competitors.

We also tend to be open with our software development and that is important. In fact, our product is called ‘OpenLab’. For instance, we have the Allotrope initiative, which is a vendor-neutral non-proprietary archive format. Agilent is one of the key leaders in that movement.

In the same vein, we also champion something called ICF - instrument control framework - our software can control other vendor instruments and vice versa. We want our customers to have that choice.

Shawn Anderson was speaking to Dr Ashley Board and Dr Karen Steward from Technology Networks.

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大多数分析化学分析的核心是数据,这是测量和监测测试主题,而且是分析设备本身的重要单位。但是,如何最好地存储它,询问它,共享并解锁最大的价值呢?有了“未来的实验室”愿景,我们很可能会看到基于数据解决方案的依赖和利用只会增长,因此重要的是有可用的解决方案和实施这些解决方案以支撑变更三月。

我们与Agilent的营销,软件和信息学部高级总监Shawn Anderson谈到了转移到以数据为中心的软件解决方案以及未来可能会有什么。


问:数据当前是孤立的,但我们正在朝着数据中心的数字生态系统迈进。在将数据放在中心的情况下,当前情况如何,最终目标是什么,这条旅程可以花多长时间?


A:
我想说的是,我们的许多客户现在已经有了某种类型的孤立解决方案,他们已经投资了,因此他们可能不会迅速移动。他们可能会进行某种类型的邻近发展,而安捷伦可以帮助他们。这些筒仓往往看起来像色谱数据系统(CD),实验室信息管理系统(LIMS),然后有时是一个经常是电子实验室笔记本(ELN)或类似的实验室执行系统。Agilent的愿景是提供刚开始的实验室,将许多这些功能结合在一起的数据系统 - 例如,LIMS和ELN与CD直接接口。Agilent于2018年5月收购了一家名为GenOHM的公司,该公司提供了一个解决方案来数字化您的实验室工作流程,将LIM与ELN(称为Slims)结合起来,用于简单的Lims。我们的计划是在接下来的12到18个月内直接与我们的CD集成。

问:With the cloud, how do you ensure that you meet the needs of the different labs that you serve?


A:
Agilent进行了广泛的市场调查,我们认为对市场进行了准确的细分,以提供各种不同类型的云解决方案。这里有些例子。首先,有较大的客户将整个CD移至云 - 我们已经做到了。第二个是使用云作为存储。

最终,对于那些较小的中型实验室而言,将来的情况将是软件即服务(SaaS)解决方案。例如,可以通过扫描可以自动连接到数据系统和云中的存储的条形码扫描条形码来插入网络中。Agilent可以为此提供帮助。我们认为这对较小和中型的实验室特别有吸引力,因为它大大减少了它们的支出并使他们迅速运行。

问:对于很多人来说,一个实验室会做些特殊的方式,因为他们总是这样做。您如何应对让人们拥抱变革和采用新系统的挑战?


A:
由于消费市场,它变得容易得多。年轻的实验室技术员可能直接从大学开始,从分析实验室开始,可能从未在工作站上安装软件。有趣的是,我们没有开车,我们的客户是。

问:您对变化的速度感到惊讶吗?


A:
是的!显而易见的是,我们客户的观点已经从“云还是没有云?”转变为“绝对云,绝对使用亚马逊和Google等提供的这些企业体系结构”。我们还看到一些客户愿意与我们共享他们的数据。这使我们能够对他们说:“我们的算法查看了您的最后20次跑步,我们注意到性能有所降低”,或者“看起来您正在进行聚糖分离,您是否知道,如果您使用这些技术,得到更好的结果?”只要有适当的安全保障措施,我们就可以通过分析进行分析并建立信任。

问:您目前是否能够使用有关使用信息来寻找趋势,例如发生常见的崩溃或故障,例如,您可以将未来的发展和改进重点放在首位?


A:
是的。我们现在提供。有一个选择加入功能,使客户能够为我们提供访问其汇总服务数据和性能数据的访问,使我们能够回到他们身边,并说:“您有三个主要应用程序,而您最大的应用程序仅使用40个应用程序您的资源百分比且容易饿了,但是您的其他两个应用程序没有,因此您是否考虑过将其中一些资源切换为最大的应用程序?”这项服务很容易获得,我们已经看到了一个实验室,其中一个实验室拥有300 GC,300 LC,对他们来说,解决方案非常有益。将来,它可能都是自动化的。

问:许多人在那里做软件。您认为真正将您放在一边,或者您说的话是独一无二的还是更好的?


A:
Agilent非常重视客户的成功。我们要确保客户正确。这是整个公司的哲学,真正的文化,我认为来自惠普时代。因此,这是让我们除了竞争对手之外的一件事。

我们也倾向于对我们的软件开发开放,这很重要。实际上,我们的产品称为“ OpenLab”。例如,我们有同素倡议,这是一种供应商中立的非专有档案格式。安捷伦是该运动的主要领导者之一。

同样,我们还倡导称为ICF-仪器控制框架的东西 - 我们的软件可以控制其他供应商仪器,反之亦然。我们希望我们的客户有选择。

肖恩·安德森(Shawn Anderson)正在与技术网络的Ashley Board博士和Karen Steward博士讲话。捷克葡萄牙直播

认识作者
灰板博士
灰板博士
编辑总监
Karen Steward PhD
Karen Steward PhD
Senior Science Writer
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