10 Apr 2020

At the virtual AAT-AD/PD Focus meeting held April 1 to 5, clinicians and funders involved in the Dominantly Inherited Alzheimer’s Network Trials Unit (DIAN-TU) fired up their home computers to discuss results from the first DIAN-TU treatment and prevention trial of Eli Lilly’s monoclonal antibody solanezumab, and Roche’s gantenerumab. DIAN-TU’s principal investigator, Randall Bateman of Washington University, St. Louis, had presented topline data analyses of the primary outcome, which was head-scratchingly negative. He also presented the first analyses of several of the trial’s biomarker measures, which were robustly positive (for a summary, see Apr 2020 conference news). What does it all mean? Should a trial this small and heterogeneous not have aimed for a Phase 3 cognitive outcome? What’s to be learned? Below are excerpts from this conversation, edited for brevity and clarity.

Moderator: Roger Nitsch, Neurimmune, Zurich
Panelists: Randall Bateman, Washington University, St. Louis
Rachelle Doody, Roche, Switzerland
Laurie Ryan, National Institute on Aging, Bethesda, Maryland
Heather Snyder, Alzheimer’s Association, Chicago
Roy Yaari, Eli Lilly and Company, Indianapolis

Nitsch: DIAN-TU increased the dose because the whole field was learning that high-dose exposure is important. Do you believe gantenerumab would have had a cognitive benefit if patients had gone on the high dose in the first two years, before they declined so much?

Doody: That the patients who were asymptomatic to start with did not get on the high dose until halfway through the observation period is a real detriment. Those who were symptomatic at the start did not get onto the high dose until they were already down into the moderate range. So the clinical question is unanswered. We hope that the symptomatic patients would gain clinical benefit if the theories of AD are correct that amyloid and tau are important drivers to the clinical syndrome. We were unable to test a long-enough, high-enough exposure in this study.

We were very pleased at the great tolerability of gantenerumab in these subjects. It raises the question of whether we could have gone higher with the dose.

Nitsch: It was gratifying to see all biomarkers that were presented moving toward normal. Brain amyloid down, CSF Aβ42 up, tau and p-tau down, and the NfL increase prevented. This shows the biology of the antibody is working. The whole field is witnessing that antibodies designed to remove amyloid do their jobs and are followed by other biomarkers going in the right direction. Why did this not translate into clinical benefit? Is there a threshold we need to hit? Do we need to go down to zero? Or is it dose exposure over time?

Bateman: We can’t answer this with the data from the trial. It’s still an outstanding question whether there is a threshold below which we need to get the amyloid before we get a cognitive/clinical benefit, or whether it is simply a time effect. And there’s a third dimension: the stage of disease at which this happens. In our trial, we can’t answer the high-dose question in early symptomatic stages because by the time we achieved the high dose, people were in advanced clinical stages. We have this open question: Could high dose have worked at an earlier stage of dementia? We could not test that.

Your threshold question we can approach in the exploratory open-label extension. What happens if you completely remove amyloid plaques, when people reach normal levels? In the duration we had participants on high dose in this trial, we did not get the majority back to normal yet. But in the OLE, we aim to get there.

On the dimension of time, we obviously need time to determine whether there is that effect. The OLE offers that additional time. It is possible that the biological effect of the antibody and the clinical benefit are separated by a delay, that you need to treat for a certain period of time for the brain to recover or stabilize in a way that manifests as a cognitive or clinical signal. I think some of the data from other trials, and our trial, suggest that you may need a duration to see downstream effects.

Yaari: About time and thresholds, Lilly has a lot of experience with prior solanezumab studies in mild AD populations. The lower dose did not hit primary in the EXPEDITION trials in sporadic AD, but there was a trend favoring solanezumab. In DIAN, unfortunately we averaged only one year at the higher dose. I wish we had more time at the high dose. The solanezumab data here is difficult to interpret, given the very small sample size and the wide variance within the disease-severity spectrum. We have asymptomatic and symptomatic patients all being tested together in the same model, and not all model assumptions were met. We will dive more into the data.

Nitsch: In clinical practice we use thresholds. We try to lower blood pressure to a certain threshold, we try to lower blood glucose to a certain threshold, we try to lower blood lipids to a certain threshold. Is that something we will see for AD as well? Will we have a centiloid value for amyloid PET, or for CSF or blood Aβ42 that is our target for clinical treatment?

Ryan: Those are unanswered questions, but certainly, the one successful trial we had on AD prevention is the SPRINT MIND trial. There, lowering blood pressure to 120 rather than 140 had cognitive benefit (Jan 2019 news). We may see the same thing with amyloid lowering.

Snyder: We do not know exactly what those measures will be. Maybe amyloid, maybe tau, maybe NfL, maybe something that has not yet been measured here. It is intriguing that with a drug that targets Aβ, we see changes in tau, NfL, and likely other measures that we might also be able to look at. Thinking about the future, maybe we will have a set of markers where we can target a threshold and later see a benefit.

Nitsch: Is the open-label extension looking at thresholds or a time frame? At the end of the day, it’s about neuronal integrity and synapse function, and those may take longer than the movement of the markers.

Doody: To answer this, we need converging data sources. We are pleased to extend exploration of this trial into OLE, but it is not a new double-blind trial that has been designed to answer these questions. We will gather information from the continued exposure of these patients, but we won’t get definitive answers. This OLE is exploratory. We hope to learn: Can we drive those biomarkers further in right direction? Can we cross the thresholds everyone is talking about? And will that correlate with a clinical signal? But without a placebo control, this OLE cannot give the definitive answer. We do have a large Phase 3 program on gantenerumab, in which we measure amyloid and tau PET and multiple biomarkers. We will need information from multiple sources to finally understand what it is that we need to achieve, by stage of disease, and how do we personalize this to each individual.

Nitsch: What lessons are we learning from this data as we design future AD and neurodegeneration trials?

Bateman: We have already made some modifications to our NextGen tau trials based on the experience with our three amyloid-based trials of solanezumab, gantenerumab, and atabecestat. We learned that it’s helpful to have parallel approaches to a target, and will continue that with tau by way of three different tau-based drug arms.

We learned that with the number of people enrolled in these trials, we can obtain clear biomarker results, however, the cognitive results are the big question for us. So the NextGen tau trials are starting with a clear outcome on biological engagement on the biomarkers.

We learned that symptomatic and asymptomatic people—though models can adapt and put their data together—behaved distinctly differently in the trial. The asymptomatic people in our trial did not decline. If you were asymptomatic, it was good to be in the trial, regardless of what drug arm you were in. These people were perfectly stable over four years. That’s an important lesson. It affects our design in DIAN-TU, but should be noted by other people who are designing prevention trials. The performance in a trial on cognitive measures may not mirror what we see in observational studies. The kinds of tests we administer in obs studies, the frequency at which they are administered, the results we obtain and the models that we build off those observational studies may not always directly apply to trial-level data, because trials are fundamentally different than observation studies. That is an important lessons learned.

Nitsch: What anti-tau treatments will be evaluated in Next-Gen DIAN trials?

Bateman: We want to bring in three classes. First, monoclonal antibodies that target specific forms of tau to prevent either its toxicity, aggregation, spread; second, gene-based treatments; third, small molecules that prevent or reverse aggregation. We have proposals under review at NIH and are already enrolling into a cognitive run-in to launch those trials in preparation for those drugs when they are ready.

Nitsch: Why don’t the data in the DIAN-TU trials mirror what was seen in the DIAN-observational study?

Bateman: I showed a case example in logical memory. Depending on how the test is given, and how often, there can be a strong learning effect. Just giving it more often can change how it performs. Other tests, though, seem to behave and were administered similarly to the observational study. So you can hypothesize that simply the people coming into the trial, the expectation they have, were by chance alone different. For example, the asymptomatic group had very little decline in the four years they were being monitored. A few did begin to decline in the fifth year, and that was observable, but very little. We hope in the OLE to see what happens when we continue to follow them. We expect that eventually these mutation carriers will decline, and the question is, do they decline at the same rate as carriers in DIAN-obs?

Some measures, both clinical and cognitive, did match well. For those, the DIAN-obs and the DIAN-TU placebo data were comparable, and the level and amount of decline of the two populations were similar. The devil is very much in the details of the specific test, how it is being given, the population that comes in, and how it is being analyzed.

Nitsch: Why did solanezumab seem to increase severity of symptoms?

Yaari: We do not know. We were surprised. But do not draw broad conclusions. It’s a small dataset, with caveats. We have a wealth of data from EXPEDITION.

Nitsch: Are the antibodies targeting the right Aβ species? Solanezumab and gantenerumab give us a comparison of two antibodies that have different binding profiles.

Yaari: At this time, we do not know anything definitive about targeting the different amyloid species. The amyloid hypothesis is alive and well. The prior experience we have in mild LOAD with solanezumab shows a trend toward benefit, so soluble Aβ could still be the right target.

Bateman: The acid test is the trial. If the drug has a target, and that target is engaged in the CNS of patients, and the patients benefit, that shows the target is useful. Making patients better is the practical evidence that validates a target.

Doody: The DIAN-TU trial was not a head-to-head comparison between gantenerumab and solanezumab. It was two trials that shared a placebo group. Different sites did different studies. There are many monoclonal antibodies directed against Aβ, and utility of each of them needs to be tested in its own trial.

Nitsch: What is the feedback from families to these study data?

Snyder: The families increasingly recognize the complexity of their disease. When DIAN-TU investigators recently shared the data with the participating families, there was overwhelming interest in the OLE. The families were clearly looking for the data to make their decision.

Nitsch: What does NIH think about this data with regard to funding future trials?

Ryan: NIA is invested. We’ve gotten a significant increase in funding in the last few years, and now have over 200 ongoing clinical trials. We are committed.

Nitsch: Will all raw data of both trials be made available in an unrestricted manner to researchers in academia and other companies?

Bateman: Data will be made available. The goal of a public-private trial is to maximally inform the field. In DIAN, we have to avoid self-identification and accidental discovery of one’s mutation status. In our observational study we use a procedure where people request data and it goes through an agreement process that has a very high approval rate for qualified investigators. We usually grant data requests within a few weeks. We will model DIAN-TU sharing on that, keeping in mind that trial integrity poses some added issues. We have to keep the trial’s primary aims intact. For example, sharing data before the end of the trial could threaten that. We will share the data in a way that meets the primary aims and protects the participants’ information so they or their relatives are not at risk. That is why we do not just post the data on the internet for everyone to browse. We have a lot of experience with this in DIAN-obs, where we have fulfilled more than 100 data requests from outside of DIAN, and will build on it for DIAN-TU.

Nitsch: As scientists we are learning tremendously from the DIAN-TU study today. In this sense this is not a failed trial. It is an exceptional public-private partnership.

Doody: DIAN is groundbreaking. The way industry, academia, NIH, philanthropy were able to collaborate was an immense advancement.

Yaari: This study, with its high level of data integrity, exemplifies how academia and industry successfully collaborate to address an unmet need.

Ryan: The execution of this trial was excellent, with impressive enrollment and completion over nearly seven years. While the primary endpoint showed no benefit, the data is providing invaluable information that advances our knowledge of the disease, and the biomarker data raise biological questions that need further study.

Bateman: This partnership between people from all over the world has been transformational from a scientific and clinical trials standpoint. The level of engagement, cooperation, helping each other, is extraordinary. That may not come out from the data we are showing today, but I want to share with the community how every team has rallied to the cause and come together to make this trial happen as best it can. That we together got this admittedly very challenging trial completed successfully is a testament to the entire field.

Confused About the DIAN-TU Trial Data? Experts Discuss

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