This innovative approach to preclinical studies is designed to reduce and refine the use of animals. We are committed to the ethical use of animals in science. Applying the same rigorous standards typically used in human clinical studies, utilizing imaging to obtain data for longitudinal measurements instead of a separate cohort, and data/resource sharing of all data collected and archived (including MRI images, behavior videos and tissue archiving) are all examples of how SPAN reduces and refines the number of animals required to answer these critical translational questions.
What is SPAN?
The Stroke Pre-Clinical Assessment Network (SPAN) seeks to conduct late-stage preclinical studies of putative neuroprotectants combined with reperfusion. SPAN utilizes a novel, adaptive, secured system for parallel testing of promising interventions designed to extend the treatment time window and/or improve outcome compared to reperfusion when combined with thrombolysis, thrombectomy or both.
Why SPAN?
SPAN was established to address a significant need in the scientific investigation of stroke treatment. In the past, a plethora of putative neuroprotectants proceeded to clinical trial based on favorable preclinical assessment, only to fail in subsequent clinical trials of human stroke patients. The recent successful development of thrombectomy for acute ischemic stroke generated considerable enthusiasm for testing treatment candidates in combination with thrombectomy. Thus, SPAN is intended to screen and select highly promising treatment candidates for possible further study in human clinical trials.
How will SPAN accomplish this task?
Using a multi-arm, multi-stage (MAMS) adaptive design, up to 6 candidate treatments will enter SPAN network testing. The primary outcome will include behavioral tests and quantitative lesion volume. Our focus in SPAN will be to assure the highest possible rigor so that any treatment candidate identified as “promising” in SPAN has a higher likelihood of success in subsequent clinical trials.
Why is SPAN important?
Stroke remains a significant burden on patients, families, and the global health care system, but treatment options remain limited. Successful therapy for stroke includes recanalization with thrombolysis (clot busters), thrombectomy (clot removal) or both. In the last 30 years, hundreds of putative neuroprotectants have been evaluated in preclinical models. The plethora of clinical failures has cost industry and governments hundreds of millions of dollars and wasted the time, talent, and efforts of hundreds of investigators and coordinators. A success in SPAN will provide a significant impetus toward renewed enthusiasm and successful clinical deployment of novel, promising neuroprotectants.
What has changed?
In the past 5 years, two significant developments raise new hope for neuroprotection: the appearance of new compounds with multiple mechanisms of action, and the advent of intra-arterial clot removal. Previously, established dogma dictated that putative neuroprotectants must have one firmly established mechanism of action, typically involving a single target. Recently, our field accepted the complexity of the ischemic cascade: that multiple deleterious pathways proceeded in parallel and that successful neuroprotectants should target multiple pathways. The SPAN effort affords the highly significant opportunity to find a promising treatment candidate, test it in human clinical trials, and then back-validate the ideal preclinical testing paradigm that correctly predicts success in clinical trials. The second significant development raising new hope for neuroprotection concerns the evolution of our treatment approach in clinical stroke. In previous clinical stroke trials with putative neuroprotectants prior to endovascular thrombectomy, up to 85% of patients did not reperfuse. Thanks to the success of endovascular thrombectomy and advanced imaging, we know exactly which subset of patients may reperfused and thus could benefit the most from a neuroprotectant. SPAN will model endovascular thrombectomy by incorporating reperfusion in the model and then testing 6 putative protective therapies.
What does SPAN add to current approaches?
Testing guidelines follow consensus statements such as STAIR. Intense analysis of preclinical development programs in stroke and neurodegeneration have identified key problems that must be addressed, starting with a variety of biases that have bedeviled animal research in general, but stroke modeling specifically: attrition bias, detection bias, performance bias, and selection bias. SPAN will significantly improve preclinical development by implementing the following critical technical innovations for the first time in a preclinical stroke testing network: central randomization, masking treatment assignment, power analysis and rational sample sizing, replication in multiple laboratories, study with key factors that impact outcome e.g., diabetes, hypertension, age, sex.
Why a network?
Simulations have clearly documented the superiority of multi-site trials over single-laboratory studies. The multi-site approach improves the external validity and should improve the likelihood of clinical success. Thus, SPAN results will significantly alter the development of stroke therapies in the future.
External Advisory Board
Pooja Khatri, MD Univ. of Cincinnati
Raul Nogueria, MD, Emory University
Marilyn Cipolla, PhD Univ. of Vermont
Mike Tymianski, MD, PhD Univ. of Toronto, NoNO Inc.
Robert Silbergleit, MD, Univ. of Michigan
Renee Martin, PhD, Medical Univ. of South Carolina
Mhairi Macrae, PhD, Univ. of Glasgow, UK
NINDS Team
NINDS Division of Neuroscience, Neural Environment Cluster:
Francesca Bosetti, PhD, Projects Scientist
Jim Koenig, PhD, Administrative Program Officer
NINDS Division of Clinical Research:
Scott Janis, PhD
Claudia Moy, PhD
Clinton Wright, MD
NINDS Director:
Walter Koroshetz, MD
Further Reading:
1. Carmichael ST, Cho S, Cipolla MJ, Corbett D, Corriveau RA, Cramer SC, Ferguson AR, Finklestein SP, Ford BD, Furie KL, Hemmen TM, Iadecola C, Jakeman LB, Janis S, Jauch EC, Johnston KC, Kochanek PM, Kohn H, Lo EH, Lyden PD, Mallard C, McCullough LD, McGavern LM, Meschia JF, Moy CS, Perez-Pinzon MA, Ramadan I, Savitz SI, Schwamm LH, Steinberg GK, Stenzel-Poore MP, Tymianski M, Warach S, Wechsler LR, Zhang JH, Koroshetz W. Translational Stroke Research: Vision and Opportunities. Stroke. 2017;48(9):2632-7. Epub 2017/07/29. doi: 10.1161/strokeaha.117.017112. PMCID: PMC5599159.
2. O'Collins VE, Macleod MR, Donnan GA, Horky LL, van der Worp BH, Howells DW. 1,026 experimental treatments in acute stroke. Ann Neurol. 2006;59(3):467-77.
3. Voelkl B, Vogt L, Sena ES, Wurbel H. Reproducibility of preclinical animal research improves with heterogeneity of study samples. PLoS Biol. 2018;16(2):e2003693. Epub 2018/02/23. doi: 10.1371/journal.pbio.2003693. PMCID: PMC5823461.
4. Sena ES, van der Worp HB, Bath PM, Howells DW, Macleod MR. Publication bias in reports of animal stroke studies leads to major overstatement of efficacy. PLoS Biol. 2010;8(3):e1000344. Epub 2010/04/03. doi: 10.1371/journal.pbio.1000344. PMCID: 2846857.
5. Macleod MR, Fisher M, O'Collins V, Sena ES, Dirnagl U, Bath PM, Buchan A, van der Worp HB, Traystman R, Minematsu K, Donnan GA, Howells DW. Good laboratory practice: preventing introduction of bias at the bench. Stroke. 2009;40(3):e50-2. Epub 2008/08/16. doi: STROKEAHA.108.525386 [pii] 10.1161/STROKEAHA.108.525386.
6. Fisher M, Feuerstein G, Howells DW, Hurn PD, Kent TA, Savitz SI, Lo EH. Update of the stroke therapy academic industry roundtable preclinical recommendations. Stroke. 2009;40(6):2244-50. Epub 2009/02/28. doi: STROKEAHA.108.541128 [pii]
10.1161/STROKEAHA.108.541128.
7. Rogalewski A, Schneider A, Ringelstein EB, Schabitz WR. Toward a multimodal neuroprotective treatment of stroke. Stroke. 2006;37(4):1129-36.
8. Crossley NA, Sena E, Goehler J, Horn J, van der Worp B, Bath PM, Macleod M, Dirnagl U. Empirical evidence of bias in the design of experimental stroke studies: a metaepidemiologic approach. Stroke. 2008;39(3):929-34. Epub 2008/02/02. doi: STROKEAHA.107.498725 [pii] 10.1161/STROKEAHA.107.498725.
9. Kilkenny C, Browne WJ, Cuthill IC, Emerson M, Altman DG. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biol. 2010;8(6):e1000412. Epub 2010/07/09. doi: 10.1371/journal.pbio.1000412. PMCID: PMC2893951.