October 1, 2019

The Value of Team Science in Alzheimer’s Disease Research

Ben Logsdon

The Value of Team Science in Alzheimer’s Disease Research

The Sage Perspective

Silos in research are slowing us down. This isn’t a revelation, but it is a rallying call for many of us who hope to overcome barriers to advancing research, especially for a disease like Alzheimer’s.

In the study of Alzheimer’s, there has been a spectacular failure in the development of therapies. All the drugs that are allegedly disease-modifying have failed in late-stage clinical trials. The thinking around what causes the disease has not moved beyond a few hypotheses that have taken root.

Related News: Bringing Open Science to Drug Discovery for Alzheimer’s

This has occurred because the scientific community has fallen for the streetlight effect: We continue to expend resources to generate new data on hypotheses that have existing promising data because it is viewed as a safe bet. Given the repeated failure of clinical applications of these hypotheses (e.g. the Amyloid hypothesis), we face the stark reality that the true nature of the disease is a quagmire of uncertainty.

Fundamental shift

Yet there are rational strategies that have been successful in other domains such as finance that the community can use to mitigate that uncertainty. Instead of continuing to accrue data on what isn’t working, we ought to systematically explore the boundaries of our collective knowledge about Alzheimer’s Disease and balance the distribution of resources across low-, medium-, and high-risk ideas. This requires a fundamental shift in how we think about doing science, because no individual contributor can perform all of the tasks necessary to expand our collective knowledge in a meaningful manner.

There are so many silos that a lot of data, new ideas, and hypotheses don’t get shared. There also is some level of distrust in the community by researchers who want to guard proprietary information for the sake of a “magic bullet.” But there is no magic bullet. If we don’t collaborate strategically and diversify our research portfolio, we will continue to fail.

We are at a critical stage in Alzheimer’s Disease research where the community and individual researchers must put aside their individual reservations and work together. We have to let go of what’s not working and acknowledge that there are potentially other factors that affect how the disease behaves. It’s imperative that fresh ideas are given adequate space to succeed and to disrupt current structures to facilitate this exchange. We have to hedge our bets.

Radically open

At Sage, I lead a team that works across several programs that are identifying new drug targets to treat Alzheimer’s disease. There are many different academic institutions that are generating high-dimensional molecular data that can be used to try to identify new genes and pathways that could be fresh drug targets. We, in the spirit of open science, help orchestrate the analytic and data coordination efforts associated with that endeavor.

Our goal is to use a data-driven approach to better understand the underlying molecular mechanisms of the disease. It’s not something that any individual group would have the resources to do effectively. So it really requires a community-driven approach. Sage is positioned to conduct the scientific coordination that can help researchers work more effectively to get at these new ideas that might lead to a successful treatment.

Our primary project is AMP-AD (Accelerating Medicine Partnership in Alzheimer’s Disease), which is a public-private partnership supported by the National Institutes on Aging. We serve as a hub for all the data that’s being generated across the project. It’s a radically open model where all the data become open once they have gone through quality control. You don’t have any publication embargoes or restrictions on data use – aside from adhering to governance standards associated with sensitive human data.

We play a role in trying to increase the transparency of all the analyses that become available. We’re also building partnerships with academic investigators to streamline how we reach a consensus about what the data are telling us about the potential causes of this disease. We want to make sure that any conclusions are consistent across different research teams, because the more generalizable a solution is, the more likely it will lead to a successful treatment.

The long view

In addition to this scientific coordination work, my group is also performing original research on Alzheimer’s Disease. In all of our research, we operate under the same open model as all of our collaborators. Practicing this open approach in our own work is important at Sage. By holding ourselves to the same standard that we ask the community to live by, we can understand and work through any pain points. In this way, we hope to lead by example. At Sage, we do have the benefit of a culture and incentive structure that emphasize the long view versus, say, maximizing revenue in the short term. Being able to think on a longer time scale affords us the ability to make decisions that improve science more materially than if we were to focus on solo – and siloed – projects.

Any approach to tackling how science is done needs to be systematic in order to have long-lasting impact. For Alzheimer’s disease, we have an opportunity to improve how therapeutic development happens. Our vision and hope is that any future compounds that may result from open research we support would be achieved faster and more efficiently, and be made available in an affordable and equitable manner.

Being radically open and collaborative isn’t easy, but operating in a silo won’t get us far enough. We have to be more intentional about team science. Lives depend on it.


Ben Logsdon

Dr. Logsdon is the Director of Neurodegenerative Research at Sage Bionetworks, where he leads consortia wide efforts to analyze ‘omic data generated in the Accelerating Medicine Partnership – Alzheimer’s Disease (AMP-AD) consortium. He also leads the Sage team’s efforts on variant prioritization for generation of new mouse models of late onset Alzheimer’s disease within the MODEL-AD consortium. Within the context of Alzheimer’s disease research, he is leading efforts to define robust and reproducible transcriptomic signatures of disease, along with building better community resources to accelerate the identification of novel targets within Alzheimer’s disease via the AMP-AD Knowledge portal (https://ampadportal.org) and Agora (https://agora.ampadportal.org).