强在一起:思想的融合和数据

Across the state line in Wisconsin, Howard Jacob is serving as the founding director of the Human and Molecular Genetics Center at the Medical College of Wisconsin. During his nearly 20-year tenure at the university, he will be part of the first team ever to use genome sequencing, or a full DNA blueprint, to diagnose and treat a patient.

Little did they know at the time, but these two PhDs working in different states on different types of science would end up crossing paths decades later. And not just cross paths, but bring their disciplines together to lead one of the largest data initiatives in the biotech industry.

1990年代初。菲尔Hajduk蹲在一个实验室在北芝加哥,伊利诺斯州,在那里,他的专注于发展小分子药物目标肿瘤细胞。试验和错误,缺乏数据的训练有素的化学家仔细研究和利用的新技术。

雅各在威斯康辛州的州界线,霍华德是作为人类的创始董事和分子遗传学中心威斯康辛医学院。在大学将近20年的任期,他将第一个团队的一部分使用基因组测序,或一个完整的DNA蓝图,诊断和治疗病人。

他们并不知道,但是这两个博士工作在不同的州在不同类型的科学最终将几十年后穿越路径。而不仅仅是交叉路径,但把他们的学科在一起导致生物科技行业最大的数据计划之一。

They liken their relationship to the same way they view science data: seemingly disparate and unrelated but in reality, different yet complementary pieces of a bigger puzzle. This has become apparent over the past year, as Hajduk and Jacob came together to tackle the next piece of the digital health revolution: data convergence.

Simply put, convergence is bringing data together. But why is this important for a biopharma company?

“The challenge many industries face, including ours, is that it’s difficult to pull out knowledge as human beings,” Jacob says. “We’re limited by how we can process mass amounts of data, so instead we’re changing everything about how we leverage and generate knowledge around data.”

快进到2021年:Hajduk刚刚庆祝AbbVie 28年推进科学,但他从板凳上毕业,现在领导着公司的研究团队的信息。在办公室在校园,雅各是纪念四年AbbVie监督基因组学研究和数据集成。

他们以同样的方式把他们的关系比作科学数据视图:看似完全不同的和不相关的,但在现实中,不同但互补的一个更大的难题。这已成为明显的在过去的一年中,Hajduk雅各一起解决下一个数字卫生革命:数据融合。

简单地说,综合各种数据融合。但是为什么这是重要的生物制药公司吗?

“包括我们在内的许多行业面对的挑战是,很难拿出知识作为人类,”雅各布说。“我们限制我们如何处理大规模的数据,所以我们改变我们如何利用并产生知识的一切数据。”

Well, now there’s enough data. And more importantly, a vision and commitment from AbbVie leadership to double down and create a better data infrastructure and enable knowledge sharing. The ultimate goal: to better treat disease and manage health care more broadly.

This commitment sparked a collaboration between every part of the company’s science organization that maintains, manages and analyzes data (read: all of them). Early discovery science. Chemistry. Genomics. Health economics & outcomes research team. Patient safety. Clinical trials. And on and on.

Each of these groups have built IT strategies, databases and processes that enable how they work. Now, the walls have come down. The past year, leaders focused on building the foundation, leaning on behind-the-scenes data engineering to create and populate a single internal platform with strong governance.

That’s important, but the real value comes a few steps after you bring the parts together, Hajduk says, because mass amounts of data alone won’t help scientists make better decisions.

“What we're building is distinct. It's not a data swamp. It's a knowledge platform,” he says. “Not only do we bring the data in and harmonize it, but we actually sit down with the subject matter experts and ask, what do those data mean? What’s the level of interpretation we can put on this data, and how do we scale that to our entire scientific community?”

数据挖掘,机器学习,人工智能。数字医疗革命的承诺一直在新闻头条多年来,整个行业。现在有什么不同吗?

好,现在有足够的数据。更重要的是,一个愿景和承诺从AbbVie领导翻下来,创造一个更好的基础设施,使知识共享数据。终极目标:更好地治疗疾病和管理医疗保健更广泛。

这一承诺引发了公司各个部门之间的协作的科学组织,维护,管理和分析数据(阅读:全部)。早期发现的科学。化学。基因组学。卫生经济学&结果研究团队。患者安全。临床试验。等等。

这些团体建立了策略,数据库和过程,使它们是如何工作的。现在,墙上有下来。过去的一年里,领导侧重于建立基础,靠在幕后数据工程创建和填充一个内部平台,并有很强的治理。

这很重要,但真正的价值是几步把零件后,Hajduk说,因为大规模的数据量就不会帮助科学家做出更好的决策。

“我们建筑是不同的。这不是一个数据沼泽。这是一个知识的平台,”他说。“我们不仅带来的数据和协调,但实际上我们坐下来与主题专家和问,这些数据是什么意思?什么水平的解释我们可以把这个数据,我们如何,我们整个科学界?”