Quantifying the difference between brain maps of humans and animal models to improve drug development

Grace Medical Institute
Lynnwood, Washington
MedicineNeuroscience
Tax Deductible
$1,600
Pledged
3%
Funded
$66,000
Goal
41
Days Left
  • $1,600
    pledged
  • 3%
    funded
  • 41
    days left

About This Project

The drug industry spends billions annually on brain diseases. But, 94% of neurological drugs that appear safe and effective in animal models fail in human trials. One explanation is the complex variation between the brains of animals and humans. In an effort to improve drug success, we propose a new way to reveal the similarity and difference between species using brain maps. Once developed, this analysis will help researchers predict drug success potential with greater accuracy.

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What is the context of this research?

In most organs, neighboring cells mediate similar functions. However, brain cells are highly diverse and organized into hundreds of functionally distinct brain areas. Because of this diversity, a detailed comparison is necessary to assure the functional similarity between human and animal brains. The lack of comprehensive data sets prevented this comparison in the past.

A brain map is a data set of where and when genes turn on or off across the entire brain and how cells are interconnected. Our team has built and analyzed brain maps for over a decade. With this project, we plan to use these brain maps to develop a new approach for comparing brains between species. When scientists know how animal brains mimic human brains, they can make better predictions for a drug’s effects in humans.

What is the significance of this project?

Healthcare costs associated with brain diseases are steeply increasing. Dementia alone accounts for nearly 1 trillion dollars worldwide. Unfortunately, only 6% of drugs get FDA approval for the brain. It costs upwards of $2.5 billion to make a new drug. This causes the prohibitive rise in drug prices. Therefore, even small advances are invaluable.

When established, our analysis can help reveal a drug’s therapeutic potential and risk earlier in the development process. Further, it could distinguish drug targets among many candidates. With these results, drug companies can focus on experiments that help reduce potential risks prior to further investment. This would lower the amount of money and time needed to bring a drug to market, increasing accessibility for patients!

What are the goals of the project?

We are establishing a new analysis method to compare the brains of mice, monkeys, and humans. The resulting data set will cover up to 200 brain areas and multiple developmental stages. We will then evaluate more than 20 anti-epileptic drug target genes and assess the degree of similarity or difference between species. Next, we will test the utility of our analysis using clinical data from anti-epileptic drugs. We will look for associations between our results and clinical outcomes, such as efficacy and side effects.

This effort will serve as an exemplar as we continue to solicit funding from public agencies, private foundations, drug companies, etc. Following this study, we will apply our approach to drug targets implicated in other brain diseases. Click here for more details.

Budget

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With a $66K budget, our research team consisting of neurobiologist, neuroanatomist, and data scientist will conduct the analysis over a 6 month period at 20-40% time (Phase-1). Because we have unique expertise and experience with brain maps, we will be able to analyze large stores of data with a modest budget in a relatively short time.

If there is additional support from the community, we will expand the project to broader areas of brain research. For example, with a total of $195K, we can conduct a comprehensive study for autism drug targets (Phase-2).

Your donation is tax deductible.

Endorsed by

Instrumental in building pioneering brain maps such as Mouse Connectivity Atlas, Seung Wook is an expert at finding the jewels within the brain maps. A key hypothesis his team is testing in this study could open up a powerful avenue for drug industry as well as disease researchers. He is stringent, meticulous, detail-oriented, extremely well organized, highly efficient, and completely trust worthy. I will have no hesitation in giving him the highest possible recommendation.

Flag iconProject Timeline

The proposed study will take approximately 6 months, starting from Nov 1, 2017. After concluding the study by the end of April, 2018, we plan to submit a manuscript to summarize the results in a scientific journal in the second half of 2018.

When we meet the first funding goal, we will present a stretch goal along with additional timelines and milestones (to be determined).

Sep 16, 2017

Project Launched

Nov 01, 2017

Start of project

Dec 15, 2017

Completion of step-1 (data preparation, alignment)

Feb 28, 2018

Completion of step-2 (assessment of AED target genes)

Mar 31, 2018

Completion of step-3 (congruence measure, summary)

Meet the Team

Seung Wook Oh, Ph.D.
Seung Wook Oh, Ph.D.
Executive Director / Principal Scientist

Affiliates

Grace Medical Institute
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John A. Morris, PhD
John A. Morris, PhD
Principal Scientist

Affiliates

Grace Medical Institute
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Team Bio

Over the last 10 years, we’ve played key roles together in creating and analyzing several large-scale brain maps, from gene to circuit and from mouse to human. Our competency is highlighted in several high-profile publications (Nature 2014; Cell 2012; PNAS 2010).

Please check our website for more information (www.grace-medical.org).

Seung Wook Oh, Ph.D.

Previously at the Allen Institute for Brain Science, my research was focused on understanding basic building blocks (gene, circuit) of brains through industrialized brain mapping projects. In particular, I pioneered a systematic circuit analysis and orchestrated interdisciplinary teams to build the foundational Mouse Connectivity Atlas. The completion of the atlas and Nature article (Oh et al., Nature 2014) garnered broad media attention, and was ranked 18th in the Discover Magazine’s top 100 stories of 2014 (Discover Magazine, NBC news, New York Times, etc.).

With nearly a decade of experience planning, building, and analyzing large-scale brain maps, I now desire to apply my skill sets to address brain diseases. At Grace Medical Institute, I envision the use of existing and future brain maps to overcome critical barriers in disease research and drug development for a broad array of central nervous system (CNS) disorders. That is, to leverage brain maps of genes and circuits to (1) identify the most relevant scientific questions and (2) explore disease-specific alterations in the brain.

I received my B.S. in chemistry and M.S. in biochemistry and molecular biology from Seoul National University in Seoul, Korea, and Ph.D. in biomedical sciences from the University of Massachusetts Medical School, where I studied the molecular mechanism of aging using the tiny worm, called C. elegans, as a model system. I was also trained as a postdoctoral fellow under the supervision of two Nobel laureates, Drs. Michael Brown and Joseph Goldstein at the UT Southwestern Medical Center, where I investigated the role of hypothalamic neurons in regulating feeding and energy homeostasis.

John A. Morris, PhD

My expertise is designing and conducting large-scale analyses of gene and protein expression across the entire brain of many species and developmental time points in order to establish functional relationships that may influence behavior and drug activity.

I helped pilot and test the developmental mouse and the adult human atlases (Hawrylycz et al., Nature 2012) at the Allen Institute for Brain Science, along with other large projects there considering the effect of strain, species, and sex on gene expression (Morris et al., PNAS 2010). By training the data annotation team in comparative molecular neuroanatomy, I supported efforts across many atlasing and data analysis projects. These cellular level analyses across the brains of humans, non-human primates, and mice, resulted in work that produced or supported several high-level publications.

Following the completion of atlas projects, I moved to the preclinical environment and directed GLP studies at SNBL USA, where specialization in non-human primate work has provided me means to develop new ways of measuring drug efficacy and safety. My experience regarding safety pharmacology alerted me to a surprising gap, whereby unexpected neurological side effects could be anticipated or mitigated by applying translational brain mapping experience to such preclinical concerns. I received a B.A. in economics at University of Tennessee and a Ph.D. in Neuroscience at Michigan State.

It is my present goal to apply my familiarity of the CNS specific data sets I helped create (and newer datasets as they become available) to tractable problems of the research community, by highlighting and exploiting translational comparisons much earlier in the discovery process. I’ve trained many people, online, in workshops, and in person, on these data sets, and hope for their continued success in streamlining efforts to address brain disease.

Additional Information

References:

1. Allen Institute for Brain Science. Allen Brain Atlas (www.brain-map.org).

2. Thomas Insel. The Global Cost of Mental Illness. National Institute of Mental Health blog (2011).

3. Alzheimer’s Disease International. World Alzheimer Report 2015.

4. The Tufts Center for the Study of Drug Development. A study on the average cost to develop and gain marketing approval for a new drug (2014 and 2016 report).

5. Ochoa et at. Antiepileptic drugs. Medscape (2016).

6. Oh et al. A mesoscale connectome of the mouse brain. Nature 508:207-214 (2014).

7. Zeng et al. Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures. Cell 149:483-496 (2012).

8. Morris et al. Divergent and nonuniform gene expression patterns in mouse brain. PNAS 107:19049-19054 (2010).


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