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Making Sense of Project Impact: Preclinical testing

As part of our effort to raise awareness during Childhood Cancer Awareness Month, we created an infographic about our newest initiative that aims to get new and better treatments to children with brain tumors: Project Impact.

Today, we want to spend some time talking about a major piece of that initiative, the so-called “preclinical testing platform.” This is represented in the infographic as a “lack of testing models that adequately predict drug response in children,” and that we are trying to change this with “data-driven models.”

So what does that all really mean? Why is it so important?

We’ve talked a little about the problem (in the seventh paragraph in this previous blog, and also in the seventh paragraph of the press release), before, but here we hope to step back and take a deeper dive.

What is a preclinical testing model?

Before a new medicine or treatment becomes available for any cancer, it must first go through the clinical trial process. The clinical trial process is when potential new therapies seeking approval are first tested in sample groups of patients to ensure they are adequately safe and effective before being made available to an entire population.

However, before a potential new medicine or treatment can even enter the clinical trial process, it must first show promise in what is called the “preclinical ” setting  – hence the name (pre – before the clinical trial process!)

In order for a cancer treatment to show promise in the preclinical setting it must be run through a number of tests. Among other things, these tests seek to determine if the medicine is getting to the tumor cell; getting there in a high-enough dose to create an effect on the tumor; doing so while harming as few healthy cells as possible; and, ultimately, whether the tumor cells stop growing and/or die.

These tests typically take part using real tumor tissue that has been obtained from patient biopsy and been engineered into a “cell line” or “cell culture” (think a petri-dish or test tube in your middle or high school biology class). These experiments in tumor cells are often referred to as in vitro (“within the glass” or “outside the body”) testing.

Typically, if in vitro testing for a potential new treatment is promising it will move on to the next step in preclinical testing, which is testing in animals (typically mice), called in vivo (“within the living” or “in the body”).

In cancer research, the goal is to make preclinical testing in cells and animals produce information (data) on how the potential new treatment interacts with a tumor in order to predict as accurately as possible what might happen if that medicine was given to a human patient with a brain tumor. So in that light, the cells and animals that are used to test these drugs in the preclinical setting are modeled as closely as possible to a tumor in a human. Hence the term preclinical testing models.

The preclinical testing platform refers to all of the different cell lines, animal models, and list of tests that will need to be performed on a potential new treatment undergoing evaluation. So for example, a preclinical testing platform might consist of, say, two different types of animal models, with 10 animals in each model, 5 different cells lines, and 6 different tests to perform on each of them.

However, we know that tumor cells outside the body and in mice both often act differently than tumors do in humans. Which brings us to the next important question…

What is the trouble with current preclinical testing models?

“…Too many basic scientific discoveries, done in animals or cells growing in lab dishes and meant to show the way to a new drug, are wrong” – Reuters, March 28, 2012

Simply put, preclinical testing models for children with aggressive forms of brain tumors currently do not adequately predict what the results will be when a drug that has been tested in cells and animals is actually tried in humans.

The facts in this regard are troubling: Even after animal studies suggest that a treatment will be safe and effective, 80% of potential therapeutics fail when tested in humans.

This grim statistic led to the prestigious scientific journal Nature Reviews Clinical Oncology to proclaim in a 2011 editorial that, “preclinical strategies to evaluate [new drugs] are suboptimal, and identifying the correct target using appropriate preclinical models will be critical to prevent further drug failures.”

In the pediatric brain tumor space, the accuracy of models of aggressive gliomas have been hindered by:

  • The fact that there are relatively few patients (~4,000 new diagnosis per year), spread out across the country
    • Which means the many pieces (tissue samples from biopsies, cell lines, mouse models, data, etc.) needed to generate a platform with statistical power to adequately predict how a potential therapy might interact with a child’s tumor are siloed in small clusters at many medical and research institutions throughout the world.
    • Which also means that most models probably have not been fully validated (re-tested by another research lab to make sure they do adequately correspond to the human tumor they are trying to replicate). This is called “characterization,” and is a regularly cited problem with disease testing models.
  • The work needed to ensure that models are as good as they can be, is considered “unglamorous” and often not the focus on grant proposals.
    • Yet, as another Nature article recently stated, “…without this upfront investment, financial resources for clinical trials are being wasted and lives are being lost.”

How does this affect the ability to get new and better treatments to children with brain tumors? Why does this really matter?

“The failure of experimental drugs that had once looked promising could have been prevented with better animal studies, according to a re-examination of past clinical trials” – Erika Check Hayden, Nature, March 2014

Issues with current preclinical models being often inadequate for, or below the standards of, the biopharmaceutical industry, means that many drug companies don’t trust that the research coming out of laboratories will be an accurate predictor of real tumor response in patients, and thus don’t often choose to take treatments into clinical trials for children with brain tumors.

Because clinical trials are typically the most expensive part of drug development, it is important that the well-resourced biopharmaceutical industry plays a part in advancing treatments into this critical, final phases of study before a new drug is approved (especially an era when the other main funder of clinical trials, the government, is spending less on biomedical research).

In some cases, biopharmaceutical companies are even hesitant to provide their library of potential drugs to researchers for preclinical testing because they are worried faulty preclinical data could erroneously make their compound look ineffective.

Further, if a company or institute does decide to take a potential treatment into a clinical trial for pediatric brain tumors, doing so with potentially insufficient preclinical data means that the basis, or rationale, for starting the clinical trial could be faulty and eventually doom that trial to failure, costing time, money, and lives in the process.

As multiple experts have written on, “the results of preclinical studies must be very robust to withstand the rigors and challenges of clinical trials (Begley & Ellis Nature. 483, 531-533, 29 March 2012).”

Steve Perrin also wrote in Nature this past May, saying, “The series of clinical trials for a potential therapy can cost hundreds of millions of dollars. The human costs are even greater: patients with progressive terminal illnesses may have just one shot at an unproven but promising treatment…Launching clinical trials without the backing of robust animal data keeps patients out of tests for other therapies that may have a better chance of success.” Or, as was more succinctly summarized by Erika Check Hayden in the same issue, “Irreproducible preclinical results can lead to a massive waste of time and money in clinical trials.”

What is Project Impact’s plan to change that?

“Clearly, [this all] makes the [National Brain Tumor Society’s] pre-clinical initiative more important,” – Dr. Maryam Foualdi, Cincinnati Children’s Hospital Medical Center

The preclinical component of Project Impact will seek to identify and catalogue all of the key tissue, cell lines, animal models, and data required to create a single network and new preclinical testing platform.

To do so, an expert Preclinical Advisory Committee featuring Dr. W.K. Alfred Yung of MD Anderson Cancer Center, Dr. Stefan Pfister of the German Cancer Research Center, and Dr. Nada Jabado of Montreal Children’s Hospital was formed to lead these efforts.

Working under Project Impact Co-chairs, Dr. Roger Packer of Children’s National Medical Center, Dr. Suzanne Baker of St. Jude Children’s Research Hospital, and Dr. Maryam Fouladi of Cincinnati Children’s Hospital Medical Center, the Preclinical Advisory Committee is driving discussions with a cross-section of researchers, biopharmaceutical companies, and government officials to determine: what models currently exist; the extent to which they have been characterized; and what characteristics are missing. [Click here to read a full summary of the latest Project Impact Working Group Meeting focused on the preclinical platform].

Once all of the “cataloging” of the models has been done, Project Impact will fund the creation of any missing pieces and/or validation efforts, as well as help create a plan to standardize the modeling and testing process for the future – which will round-out the new, optimized platform. This work, in sum, will ensure that in the future that preclinical research in the pediatric brain tumor field is producing better, more accurate results, which in turn will produce the data needed to move more potential treatments into clinical trials for children with brain tumors; clinical trials that are based on sound science and have a better chance of gaining much needed approvals.

The work will also be ‘self-fulfilling,’ in a way; meaning that the more trust biopharmaceutical companies have in preclinical testing as a result of Project Impact’s efforts, the greater the likelihood is that they will make more of their drugs available to be tested for pediatric brain tumor research.

In essence, Project Impact will improve the effectiveness of preclinical drug testing models with cutting edge science and a renewed focus on coordination between scientists and research sites around the world. The result will be more access to drugs for testing, and more potentially promising drugs entering clinical trials and faster.

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