I-SPY 2 Breast Cancer Clinical Trial
Highly Anticipated Multi-Agent Trial Opens at Major U.S. Medical Sites
Groundbreaking Public-Private Collaboration Combines Personalized Medicine and Novel Trial Design to Develop Potentially Life Saving New Breast Cancer Drugs
GoogleNews.com, March 18, 2010 – Researchers are taking a new radical approach to the treatment of breast cancer that will hopefully speed up discoveries and bring better treatments to patients. Three companies have started a cooperative project and are joining forces with the government to try to fine tune breast cancer treatment. It is a $26 million trial set to last five years.
Jessica Galloway, a mother of three small children, was diagnosed with an aggressive form of breast cancer. At the time of her diagnosis she says she “was so terrified – I would’ve done anything.” What she ended up doing was joining a clinical trial she believes will save her life. The trial is called the I-SPY2 (short for Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis).
This trial has come about because researchers learned every breast cancer is different. Drugs that work for some women are completely ineffective in others. In this trial, they are using genetic biomarkers to test five drugs and create treatments specific to each patient. It is a personalized medicine approach that could bring experimental treatments to high-risk women much sooner.
The Biomarkers Consortium, a unique public-private partnership that includes the U.S. Food and Drug Administration (FDA), the National Institutes of Health (NIH), and major pharmaceutical companies, led by the Foundation for the National Institutes of Health (FNIH), today announced the launch of a highly anticipated clinical trial to help screen promising new drugs being developed for women with high risk, fast-growing breast cancers—women for whom an improvement over standard treatment could dramatically change the odds of survival.
“A considerable advantage for trial participants in I-SPY 2 is that drugs and drug combinations can be given to more patients in the trial as soon as they are proven to be clearly beneficial”
The I-SPY 2 trial will employ a groundbreaking clinical trial model that uses genetic or biological markers (“biomarkers”) from individual patients’ tumors to screen promising new treatments, identifying which treatments are most effective in specific types of patients. In addition, an innovative adaptive trial design will enable researchers to use early data from one set of patients to guide decisions about which treatments might be more useful for patients later in the trial, and eliminate ineffective treatments more quickly.
“I-SPY 2 promises to leverage convergence of progress on a number of research fronts to speed the evaluation of promising new breast cancer drugs using molecular cancer biomarkers to identify those agents that are effective in specific subpopulations of breast cancer patients,” said Anna D. Barker Ph.D., Deputy Director, National Cancer Institute, and Co-Chair of The Biomarkers Consortium Cancer Steering Committee. “This will allow us to finally design advanced, smaller and less expensive Phase III trials that test the right drugs in the right patients.”
The large-scale trial involves a unique collaboration by scientists from the National Cancer Institute (NCI), FDA, and nearly 20 major cancer research centers across the country. Study results will be made broadly available to the entire cancer research and development community.
“The I-SPY 2 trial explores a whole new way to rapidly screen new cancer treatments and match the therapy to specific markers,” said Janet Woodcock, M.D., Director, Center for Drug Evaluation and Research at the U.S. Food and Drug Administration. “Developing individualized medicines needs a solution bigger than any one group can generate. The Biomarkers Consortium is a public-private collaboration of scores of organizations working together to achieve this critical mission. It is a model for the future and FDA is proud to be a founding member.”
I-SPY 2 has the potential to significantly reduce the cost of drug development and speed the process of screening drugs with the goal of bringing safe and effective new drugs to market more efficiently. Currently, it takes over $1 billion, 12 to 15 years, and thousands of patient volunteers to get a single drug to market. I-SPY 2 was developed to allow the activity of drugs to be assessed much earlier in the research process, potentially enabling drugs to be developed and approved using fewer patients, less time and far fewer resources. The goal is to shave several years and hundreds of millions of dollars off the current process.
The I-SPY 2 trial will focus on treatment in the neoadjuvant therapy setting, in which chemotherapy is given to patients to reduce tumor size before surgery. All patients will receive the current standard of care and most participants will receive one investigational drug. A distinctive feature of the trial is that it will screen multiple drugs from multiple companies—up to 12 different cancer drugs over the course of the trial. In order to do this, FNIH received a master Investigational New Drug (IND) approval from the FDA—which allows the I-SPY 2 TRIAL team to graduate, drop and add drugs seamlessly throughout the course of the trial without having to stop the trial to write a whole new protocol. This will dramatically reduce the time it takes to move from one drug to another in the trial.
Five new investigational agents currently in development by three major pharmaceutical companies have already been selected for testing as part of the first phase of the trial, and will be donated by the companies with each agent representing a different drug class or type of chemical mechanism for attacking cancer. The first agents expected to be tested include:
- ABT-888 (veliparib), a PARP inhibitor being developed by Abbott Laboratories, Abbott Park, IL
- AMG 655 (conatumumab), an APO/TRAIL inhibitor and AMG 386, an angiogenesis inhibitor, both under development at Amgen, Thousand Oaks, CA
- CP-751,871 (figitumumab), an IGFR inhibitor and HKI-272 (neratinib), a Pan ErbB inhibitor both under development at Pfizer, Inc., New York, NY
I-SPY 2 will be coordinated by two principal investigators, Laura Esserman, M.D., M.B.A., Professor and Director, Carol Franc Buck Breast Care Center at the University of California, San Francisco (UCSF), and Donald Berry, Ph.D., Professor and Chair, Department of Biostatistics, Division Head, Division of Quantitative Sciences at The University of Texas M.D. Anderson Cancer Center. Clinical operations of the trial will be managed by Angie DeMichele, M.D., M.S.C.E., Associate Professor of Medicine and Epidemiology of the Abramson Cancer Center at the University of Pennsylvania Medical Center. Nola Hylton, Ph.D., Professor of Radiology and Director of the Breast MRI Research Program at UCSF developed new tools to use MRI as a quantitative measure of response to therapy developed in a previous research study, I-SPY 1; these tools will be an integral part of the I-SPY 2 trial and will help validate whether MRI tumor volume change, rather than surgery, can be used as a way of determining patients’ response to treatment.
“I-SPY 2 will provide a path to personalized medicine,” said Dr. Esserman, a breast cancer surgeon and researcher at UCSF. “The collaborative power behind this trial is truly transformational for breast cancer patients and for cancer research as a whole. We have set up a system where everyone can learn faster and, together, we can dramatically reduce the amount of time and the cost to bring those drugs to market that can make a difference in whether women live or die.”
“A considerable advantage for trial participants in I-SPY 2 is that drugs and drug combinations can be given to more patients in the trial as soon as they are proven to be clearly beneficial,” added Dr. Berry, who supervised development of the innovative Bayesian adaptive design for I-SPY 2. “By the same token, drugs that are ineffective in the trial can be dropped just as quickly, which increases the safety of the study.”
I-SPY 2 is expected to cost approximately $26 million over five years. Funding will come from a variety of sources, and Safeway, Inc., one of the largest food and drug retailers in North America, has stepped up as a significant seed funder. The corporation will contribute a sizeable portion of proceeds from the Safeway Foundation’s annual chain-wide October Breast Cancer Awareness fundraising initiative to I-SPY 2. A major foundational investment has also been secured from Johnson & Johnson, and the project is being developed in part with funds from Genentech and Lilly. FNIH is actively working to raise the remaining funds from pharmaceutical and other companies, non-profit cancer organizations and philanthropic foundations and individuals.
I-SPY 2 has benefited from the unprecedented involvement of dozens of breast cancer advocates in helping to design the trial. The advocates—many of them former patients—have helped create brochures, a website, and DVD to inform patients about the trial. They have worked to ensure that the design of the trial is as convenient for patients as possible.
All results from the trial will be published by the investigators via articles in peer-reviewed scientific journals. The large amount of valuable data expected to be generated by the project will be stored in a database at UCSF and M.D. Anderson using tools developed as part of the NCI’s Cancer Bioinformatics Grid (caBIG) initiative. In order to maximize public health benefit, the non-profit Foundation for the NIH will serve as a trusted third party to manage data and intellectual property arising from the trial.
FNIH will manage the trial as part of The Biomarkers Consortium, a public-private biomedical research partnership that endeavors to develop and qualify biomarkers to speed the development of medicines and therapies for detection, prevention, diagnosis, and treatment of disease and improve patient care. Members of the Consortium include over fifty partners including the NIH, FDA, the Pharmaceutical Research and Manufacturers of America (PhRMA), the Centers for Medicare & Medicaid Services, the Biotechnology Industry Organization (BIO), major pharmaceutical companies, and numerous non-profit medical research organizations.
Up to 20 of the nation’s leading cancer centers, including many of NCI’s Comprehensive Cancer Centers, will recruit and treat patients as part of the trial. Currently selected centers include:
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
- University of Minnesota Medical Center, Minneapolis, MN
- Moores UC San Diego Cancer Center, University of California, San Diego, La Jolla, CA
- The University of Texas M.D. Anderson Cancer Center, Houston, TX
- University of Colorado Cancer Center, Aurora, CO
- Mayo Clinic, Scottsdale, AZ
- Mayo Clinic, Rochester, MN
- OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR
- Inova Health System, Falls Church, VA
- The University of Chicago Comprehensive Cancer Center, Chicago, IL
- The Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX
- The USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA
- Winship Cancer Institute of Emory University, Atlanta, GA
- The University of Kansas Cancer Center, Kansas City, KS
- Cardinal Bernardin Cancer Center, Loyola University Chicago Health System, Maywood, IL
Technologies from Agendia (Huntington Beach, CA) and Sentinelle Medical Inc. (Toronto, Canada) will be used to measure biomarkers in the trial.
For more information:
Clinical Pharmacology & Therapeutics 86, 97–100 (1 July 2009);
I-SPY 2: An Adaptive Breast Cancer Trial Design in the Setting of Neoadjuvant Chemotherapy; AD Barker, CC Sigman, GJ Kelloff, NM Hylton, DA Berry & LJ Esserman; http://www.nature.com/clpt/journal/v86/n1/full/clpt200968a.html
About the Foundation for the NIH
The Foundation was established by the United States Congress to support the mission of the NIH – improving health through scientific discovery. The Foundation identifies and develops opportunities for innovative public-private partnerships involving industry, academia, and the philanthropic community. A non-profit, 501(c)(3) corporation, the Foundation raises private-sector funds for a broad portfolio of unique programs that complement and enhance NIH priorities and activities. The Foundation’s Web site address is http://www.fnih.org.
Michael Stravato for The New York Times
Dr. James R. Lupski, a medical geneticist with a nerve disease, had his whole genome decoded
The New York Times, March 17, 2010, by Nicholas Wade – Two research teams have independently decoded the entire genome of patients to find the exact genetic cause of their diseases. The approach may offer a new start in the so far disappointing effort to identify the genetic roots of major killers like heart disease, diabetes and Alzheimer’s.
In the decade since the first full genetic code of a human was sequenced for some $500 million, less than a dozen genomes had been decoded, all of healthy people.
Geneticists said the new research showed it was now possible to sequence the entire genome of a patient at reasonable cost and with sufficient accuracy to be of practical use to medical researchers. One subject’s genome cost just $50,000 to decode.
“We are finally about to turn the corner, and I suspect that in the next few years human genetics will finally begin to systematically deliver clinically meaningful findings,” said David B. Goldstein, a Duke University geneticist who has criticized the current approach to identifying genetic causes of common diseases.
Besides identifying disease genes, one team, in Seattle, was able to make the first direct estimate of the number of mutations, or changes in DNA, that are passed on from parent to child. They calculate that of the three billion units in the human genome, 60 per generation are changed by random mutation — considerably less than previously thought.
The three diseases analyzed in the two reports, published online Wednesday, are caused by single, rare mutations in a gene.
In one case, Richard A. Gibbs of the Baylor College of Medicine sequenced the whole genome of his colleague Dr. James R. Lupski, a prominent medical geneticist who has a nerve disease, Charcot-Marie-Tooth neuropathy.
In the second, Leroy Hood and David J. Galas of the Institute for Systems Biology in Seattle have decoded the genomes of two children with two rare genetic diseases, and their parents.
More common diseases, like cancer, are thought to be caused by mutations in several genes, and finding the causes was the principal goal of the $3 billion human genome project. To that end, medical geneticists have invested heavily over the last eight years in an alluring shortcut.
But the shortcut was based on a premise that is turning out to be incorrect. Scientists thought the mutations that caused common diseases would themselves be common. So they first identified the common mutations in the human population in a $100 million project called the HapMap. Then they compared patients’ genomes with those of healthy genomes. The comparisons relied on ingenious devices called SNP chips, which scan just a tiny portion of the genome. (SNP, pronounced “snip,” stands for single nucleotide polymorphism.) These projects, called genome-wide association studies, each cost around $10 million or more.
The results of this costly international exercise have been disappointing. About 2,000 sites on the human genome have been statistically linked with various diseases, but in many cases the sites are not inside working genes, suggesting there may be some conceptual flaw in the statistics. And in most diseases the culprit DNA was linked to only a small portion of all the cases of the disease. It seemed that natural selection has weeded out any disease-causing mutation before it becomes common.
The finding implies that common diseases, surprisingly, are caused by rare, not common, mutations. In the last few months, researchers have begun to conclude that a new approach is needed, one based on decoding the entire genome of patients.
The new reports, though involving only single-gene diseases, suggest that the whole-genome approach can be developed into a way of exploring the roots of the common multigene diseases.
“We need a way of assessing rare variants better than the genomewide association studies can do, and whole-genome sequencing is the only way to do that,” Dr. Lupski said.
With 10 genomes of healthy humans sequenced, Dr. Gibbs, a specialist in DNA sequencing, decided it was time to decode the genome of someone with a genetic disease and asked his colleague Dr. Lupski to volunteer.
Mutations in any of 39 genes can cause Charcot-Marie-Tooth, a disease that impairs nerves to the hands and feet and causes muscle weakness.
Fifty thousand dollars later, Dr. Lupski turned out to have mutations in an obscure gene called SH3TC2. The copy of the gene he inherited from his father is mutated in one place, and the copy from his mother in a second.
Both his parents had one good copy of the gene in addition to the mutated one. A single good copy can generate enough, or nearly enough, of the gene’s product for the nerves to work properly. Dr. Lupski’s mother was free of the disease and his father had only mild symptoms.
In the genetic lottery that is human procreation, two of their eight children inherited good copies of SH3TC2 from each parent; two inherited the mother’s mutation but the father’s good copy and are free of the disease; and four siblings including Dr. Lupski inherited mutated copies from both parents. These four all have Charcot-Marie-Tooth disease. The results are reported in The New England Journal of Medicine.
In Seattle, Dr. Hood and Dr. Galas have also applied whole-genome sequencing to disease. They analyzed the genome of a family of four, in which the two children each have two single-gene diseases, called Miller syndrome and ciliary dyskinesia. With four related genomes available, the researchers could identify the causative genes. They also improved the accuracy of the sequencing because DNA changes that did not obey Mendel’s rules of inheritance could be classed as errors in the decoding process.
The Seattle team believes whole-genome sequencing can be applied to the study of the common multigene diseases and plans to sequence more than 100 genomes next year, starting with multigenerational families.
The family whose genomes they report in Science were sequenced by a company with a new DNA sequencing method, Complete Genomics of Mountain View, Calif., at a cost of $25,000 each. Clifford Reid, the chief executive, said that the company was scaling up to sequence 500 genomes a month and that for large projects the price per genome would soon drop below $10,000. “We are on our way to the $5,000 genome,” he said.
Dr. Reid said the HapMap and genomewide association studies were not a mistake but “the best we could do at the time.” But they have not yet revolutionized medicine, “which we are on the verge of doing,” he said.
Dr. Goldstein, of Duke University, said the whole-genome sequencing approach that was now possible should allow rapid progress. “I think we are finally headed where we have long wanted to go,” he said.
The U.S. Food and Drug Administration today announced the approval of the Esteem – an implanted hearing system used to treat moderate to severe sensorineural hearing loss, a type of permanent hearing loss.
FDA NEWS RELEASE
For Immediate Release: March 17, 2010
Esteem approved to treat sensorineural hearing loss
The U.S. Food and Drug Administration today announced the approval of the Esteem – an implanted hearing system used to treat moderate to severe sensorineural hearing loss, a type of permanent hearing loss.
Sensorineural hearing loss is usually caused by genetic factors or damage to the inner ear resulting from noise, viral infections, or aging. The results are reductions in perception of sounds and in the ability to understand speech.
This differs from conductive hearing loss, which occurs when sound waves cannot transmit well through the outer or middle ear or both. Medical or surgical treatment can often restore hearing in people with a conductive hearing loss, which can be caused by earwax, fluid in the middle ear space, or a punctured eardrum.
The Esteem system consists of external testing and programming instruments and three implantable components: a sound processor, sensor, and driver. The sensor senses vibrations from the eardrum and middle ear bones and converts these mechanical vibrations into electrical signals, which are then sent to the sound processor, which amplifies and filters the signal to compensate for the individual patient’s hearing loss. The driver converts the enhanced electrical signal back to vibrations, which are then transmitted into the inner ear where they are perceived as sound.
“The approval of Esteem provides patients with an option to alleviate their hearing loss by using a device with no readily visible external components,” said Jeffrey Shuren, M.D., J.D., director of the FDA’s Center for Devices and Radiological Health.
The system is designed to alleviate the effects of hearing loss in patients ages 18 years and older. Other criteria for the device include: stable bilateral sensorineural hearing loss, a normally functioning Eustachian tube, and normal middle ear anatomy. A patient’s ability to understand speech using Esteem should be similar to that of conventional hearing aids.
In a multicenter clinical study of Esteem versus pre-implant hearing aids, 93 percent of Esteem recipients scored equal to or better than their pre-implant hearing aids on a speech intelligibility test. Seven percent scored less than with their pre-implant hearing aids, and 56 percent scored better than with their pre-implant hearing aids.
Seven percent of participants experienced facial paralysis, and 42 percent experienced taste disturbance, both of which are results of the surgical procedure necessary to implant the device. The majority of these adverse events resolved during the one-year study period.
As a condition of FDA approval, Esteem manufacturer, Envoy Medical Corporation of St. Paul, Minn., must conduct two post-approval studies. In one study, Envoy must continue to follow-up on 61 subjects from the original study for five years to study safety and effectiveness. Another study of 120 newly enrolled subjects will include an evaluation of the incidence of facial paralysis at one month after implantation, and evaluate the effectiveness of Esteem five years after implantation.
For more information:
Dec. 18, 2009 Ear, Nose and Throat Devices Panel Meeting:
FDA’s Center for Devices and Radiological Health—Hearing Aids
GoogleNews.com, CNNMoney.com, March 18, 2010 – Cord Blood America (OTCBB: CBAI) TheMarketFinancial.com, the news portal which covers the latest Wall Street developments while delivering financial and investment intelligence to a community of highly informed investors, has issued a special independent research coverage on Cord Blood America (OTCBB: CBAI).
Cord Blood America recently held a conference call with TheMarketFinancial.com, in which Founder, Chairman and CEO, Mr. Matthew L. Schissler discussed several new and pre-existing company developments, at the forefront being: Organic Growth, Acquisitions, and Diversification of Revenue Streams.
The company is expecting to file the yearly report within the next thirty business days, and was proud to announce that their Debt is now listed as less than $1M USD with any other additional obligations being rather insignificant.
The highlight of the interview came at the very end where the Chairman & CEO expressed his desires and anticipations of Cord Blood America becoming the number one stem cell storage company in the world, and strongly believes they will get there through continued sound business practices. “In five years I’d like to think that we’re positioned as one of the top five stem cell storage companies in the world. My goal is to be number one, I want Cord Blood America to truly store biologics because it is a very strong annuity model,” noted Mr. Schissler.
To listen in on the exclusive interview held by TheMarketFinancial, visit this link: http://www.themarketfinancial.com/cord-blood-america-aims-to-be-number-one-stem-cell-storage-company-in-the-world-otccbai/1869.
GoogleNews.com, Bio-ITWorld.com, March/April 2010, by Kevin Davies – According to PubMed, the first use of the term “personalized medicine” occurred back in 1990. The second happened a full ten years later. Since then, close to 1000 research papers and review articles have coined the term. Somehow, I expected the tally to be much larger, given how the concept of personalized medicine is so integral to our own health and that of the pharmaceutical industry.
There are many technological and cultural drivers of personalized medicine. In part it is fueled by the enabling technology of genomics, proteomics, model building, and molecular diagnostics, all of which offer the hope of providing consumers with predictive and preemptive information to manage their own health, or select from drugs (or drug dosages) better tailored to their genetic profile. Two years ago, we published one of the most exciting developments in that arena, the discovery of the KRAS biomarker that impacts the delivery of drugs such as Amgen’s Vectibix (see, “Amgen’s Personalized Medicine Story,” Bio•IT World, April 2008). It was also a recognition that the pharmaceutical industry’s blockbuster model is on life support, with the low-hanging fruit already plucked and safety risks emerging from drugs with broad indications aimed at a hugely diverse cross-section of the population. “There is no such thing as a safe drug,” Duke University’s Allen Roses said famously a few years ago, and it behooves the drug maker to know as much about its target population as possible, both to enhance safety and to expedite passage through the clinic.
Personalized medicine is the subject of this issue’s special report (see pages 27-38), in which we look at fascinating initiatives such as the Ignite Institute for Individualized Health and the Beyond Batten Disease Foundation, as well as air the views of a quartet of industry experts, consultants, and evangelists.
Personalized medicine is also the subject of two timely books aimed at a broad readership. The Language of Life is Francis Collins’ follow-up to his best-selling The Language of God, in which he rectified his twin beliefs in science and religion. Collins, the new director of the National Institutes of Health, is a medical doctor, a gene hunter, and was famously “the field marshal” of the Human Genome Project. He wrote The Language of Life during a sabbatical between his long tenure at the National Human Genome Research Institute and his new appointment.
In customarily lucid fashion, Collins provides an enjoyable tour of the latest trends and controversies in personalized medicine, including the prospects for consumer genomics—Collins divulges some surprising information about his own genetic profiles obtained under a pseudonym—and designer drugs. The Language of Life is aimed at a large audience, and deserves to reach one. Ironically (and unfortunately) his federal appointment curtails his ability to promote the work.
Another excellent book just on the market is The Decision Tree, by Thomas Goetz, the deputy editor of Wired. One blogger suggested an alternative title: What to Expect When You’re Expecting a Long Life. Goetz’s thesis, which he laid out in the Huffington Post last year, is that personalized medicine isn’t just about choosing the right drugs at the right dose for the right patient. “It’s also about data—our personal data, the stuff in our medical records, as well as less clinical information like how much sleep we get or how often we exercise.”
Goetz lays out three rules for improving medicine: 1) Early is better than late; 2) Let data do the work; and 3) Openness is a powerful thing. He argues that our medical data can personalize our health care immediately, fed back into a virtual flowchart that we can construct to monitor and improve our health and lifestyle. There are short but insightful chapters on the problems and challenges facing drug development, but as Goetz says, “real personalized medicine should begin long before we’re faced with pharmacology.”
Goetz has a master’s in public health from UC Berkeley, which was doubtless influential in shaping his ideas. Although he comes from a family of physicians and health care providers, Goetz is adamant that, “when information technology offers so much assistance to people facing health care issues, our health is too important to leave to an archaic, insular, and information-poor structure. If there’s no longer a need to rely solely on a doctor’s advice for treatment and care, why should we be expected to artificially limit our options?”
March 18, 2010 – Rudolf Jaenisch, Ph.D, Founding Member of The Whitehead Institute and Professor of Biology at the Massachusetts Institute of Technology will give the Keynote presentation at GTCbio’s 6th Stem Cell Research & Therapeutics Conference, May 27-28, 2010 in Boston, MA.
Rudolf Jaenisch, Ph.D, Founding Member of The Whitehead Institute and Professor of Biology at the Massachusetts Institute of Technology will give the Keynote address entitled “Commercialization of Regenerative Medicine: ES cells, iPS cells and personalized medicine: Technical Challenges.” at GTCbio’s 6th Annual Stem Cell Research & Therapeutics Conference on May 27-28, 2010 in Boston, MA.
Dr. Jaenisch will discuss the recent demonstration of in vitro reprogramming using transduction of 4 transcription factors by Yamanaka and colleagues and the major questions regarding the mechanism of in vitro reprogramming that need to be understood. The progress in using iPS cells for therapy and for the study of complex human diseases will be summarized by Dr. Jaenisch as well.
Other notable presenters at the conference include Katy Spink, Vice President of Operations for Geron, and Tracey Lodie, Director of Stem Cell Biology at Genzyme.
GTCbio’s 6th annual conference on Stem Cell Research and Therapeutics provides stem cell researchers with a comfortable environment to exchange ideas and brainstorm on novel pathways to discovery. Leading experts in the field will present unreleased information and attendees will learn the most up-to-date developments in this arena. For more information visit gtcbio.com/conferenceDetails.aspx?id=145
Rudolf Jaenisch (1942- ) is a biologist at MIT. He is a pioneer of transgenic science, in which an animal’s genetic makeup is altered. Jaenisch has focused on creating transgenic mice to study cancer and neurological diseases.
Jaenisch’s first breakthrough occurred in 1974 when he and Beatrice Mintz showed that foreign DNA could be integrated into the DNA of early mouse embryos. They injected retrovirus into early mouse embryos and showed that leukemia DNA sequences had integrated the mouse genome and also to its offspring. These mice were the first transgenic mammals in history.
Jaenisch is a leader in the field of therapeutic cloning, also known as nuclear transfer, in which the genetic information from one cell is transplanted into an unfertilized egg that has had its DNA removed. When it is placed in a Petri dish, the egg develops into a blastocyst from which stem cells can be harvested. Jaenisch’s therapeutic cloning research deals exclusively with mice, but he is an advocate for using the same techniques with human cells in order to advance embryonic stem cell research. However, Jaenisch opposes human reproductive cloning, where the egg is placed into the uterus of a female, with the hope that it will develop into a fetus.
Jaenisch received his doctorate in medicine from the University of Munich in 1967. He was head of the Department of Tumor Virology at the Heinrich Pette Institute at the University of Hamburg. He has co-authored more than 300 research papers and has received numerous prizes and recognitions including an appointment to the National Academy of Sciences in 2003. He is currently a member of the Whitehead Institute and a Biology professor at the Massachusetts Institute of Technology (MIT). He participated in the 2004 science conference on human cloning at the United Nations and serves on the science advisory boards of the Genetics Policy Institute and Stemgent.
March 2010 Report
Failure to pass a significant national reform package could have unpleasant consequences for the nation’s healthcare system and its middle class. Ten million additional Americans could become uninsured in just five years, and government healthcare spending for the poor could more than double by 2020, according to a new report prepared by the Urban Institute for the Robert Wood Johnson Foundation (RWJF) in Princeton, N.J.
“Families and individuals across this country are already stretched beyond their means. They simply cannot afford to see their insurance costs rise by more than a third in just five short years,” says Risa Lavizzo-Mourey, RWJF president and CEO. “This report paints a grim picture for the future of our nation if we fail to make health insurance more affordable for all Americans, while also reducing healthcare costs.”
Urban Institute analysts used a simulation model to assess the best-case, intermediate-case and worst-case scenarios for the national changes in coverage patterns and healthcare costs that will occur from 2010 to 2020 without major reforms. The middle class will be hit the hardest under all three economic scenarios.
This year, approximately 49.4 million people have no health coverage. In the worst-case scenario, the number of uninsured would jump to 59.7 million by 2015 and to 67.6 million by 2020. The uninsured rate for middle-class families earning roughly $40,000 to $75,000 a year would rise to 28 percent in 2020, up from 19 percent in 2010. Overall, the percentage of uninsured people from families with incomes above $40,000 would increase from 44 percent to 53 percent in 2020.
In the worst-case scenario, premiums for both single and family policies would more than double by 2020, rising from $4,800 to $10,300 for single policies and from $12,100 to $25,600 for family policies. Employer spending on premiums would increase by 98 percent, jumping from $430 billion in 2010 to $851 billion in 2020. As a result, small and medium-sized employers would stop offering coverage benefits to employees, say the analysts.
These skyrocketing costs would impose heavy strains on government healthcare programs. Medicaid and Children’s Health Insurance Program (CHIP) enrollment would increase from 45.4 million in 2010 to 58.2 million in 2020, an increase of 12.8 million nonelderly Americans. Medicaid and CHIP spending for the nonelderly would grow 108 percent from $278 billion in 2010 to $576 billion in 2020. In addition, uncompensated care costs would more than double, growing from $64 billion in 2010 to $140 billion in 2020.
Funded by The Robert Wood Johnson Foundation, the Kaiser Commission on Medicaid and the Uninsured
Read the full report here.
The U.S. House of Representatives and the U.S. Senate have passed separate comprehensive health reform bills, but enactment of a final law remains uncertain. Last year, we reported on the economic implications for the nation and individual states if the health reform effort were to fail. In this paper, we update our earlier national analyses. We present new findings on the composition of the uninsured in 2020 without reform, the offers of health benefits by employers, and the increase in costs to different payers.
This report makes clear that the cost of failure would be high and the status quo is probably unsustainable. The analysis shows that if federal reform efforts fail, over the next decade, the percent of the population that is uninsured will increase, employer-sponsored coverage will continue to erode, spending on public programs will balloon, and individual and family out-of-pocket costs will rise.
Using the Urban Institute’s Health Insurance Policy Simulation Model, we examined the effects of maintaining the status quo on coverage and costs for three scenarios:
1. Worst case — slow growth in incomes and continuing high growth rates for health care costs;
2. Intermediate case — somewhat faster growth in incomes, but a lower growth rate for health care costs;
3. Best case — full employment, faster income growth, and even slower growth in health care costs.
Under any scenario, the analysis shows a tremendous economic strain on individuals and employers of all sizes. While all income levels would be affected, middle-income families would be hardest hit. Within 10 years, under the worst-case scenario, we estimate that:
»»The number of uninsured Americans would increase from 49.4 million in 2010 to 59.7 million in 2015 and 67.6 million in 2020. If states were to cut back eligibility for public coverage or make the enrollment process more difficult, the number of uninsured would be even higher. Even in the best case, the number of uninsured would rise to 57.9 million in 2020.
»»A larger share of the uninsured would come from middle- and higher-income families. The share of the uninsured from families with incomes higher than 200 percent of the federal poverty level (FPL) would rise from 44 percent to 56 percent in 2020.
»»Premiums would become increasingly expensive for employers and their workers. Premiums for both single and family policies would more than double by 2020, increasing from $4,800 to $10,300 for single policies and from $12,100 to $25,600 for family policies. Even in the best case, single premiums would rise to $7,800 and family premiums would rise to $19,500 by 2020, increasing much faster than incomes.
»»Offers of coverage would fall significantly for workers in small and medium firms. Small firm workers would see offer rates almost cut in half, dropping from 41 percent to 23 percent in 2020. Workers in medium-size firms would see offer rates fall from 90 percent to 75 percent. Overall, the rate
of employer sponsored insurance coverage would fall from 56 percent in 2010 to 48 percent of nonelderly Americans in 2020. Even in the best case, the rate of employer sponsored insurance coverage would fall to 53 percent in 2020.
»»Medicaid and Children’s Health Insurance Program (CHIP) enrollment and costs would increase substantially. Enrollment would increase from 45.4 million in 2010 to 58.2 million in 2020, an increase of 12.8 million nonelderly Americans. Medicaid and CHIP spending for the nonelderly would increase from $278 billion in 2010 to $576 billion in 2020, an increase of 108 percent. Even in the best case, spending would increase by 59 percent to $442 billion in 2020.
»»Employers would see large increases in premium costs. Employer premium spending would increase from $430 billion in 2010 to $851 billion in 2020, a 98 percent increase. Even in the best case, employer premium spending would increase by 67 percent in ten years. These increases would be even higher if employer coverage rates were to hold steady over this period rather than decline as predicted.
»»Uncompensated care costs would more than double. The cost of uncompensated care would increase from $64 billion in 2010 to $140 billion in 2020. In the best case, the cost of uncompensated care would increase by 74 percent and total $111 billion in 2020. Together with increased spending on Medicaid and CHIP, this would mean higher federal, state, and local taxes even without reform.
»»Health care costs paid directly by families would increase significantly. Individual and family spending on premiums and out-of-pocket health care costs would increase from $315 billion in 2010 to $564 billion in 2020. In the best case, these costs would rise to $471 billion by 2020.
The Cost of Failure to Enact Health Reform: 2010–2020 3
The U.S. House of Representatives and the U.S. Senate have passed separate comprehensive health reform bills, but enactment of a final law remains uncertain.1 Last year, we reported on the economic implications for the nation and individual states if the health reform effort were to fail.2, 3 We estimated changes in private and public coverage and the number of uninsured. Further, we estimated the increase in spending by businesses, individuals, and government. In this paper, we update our earlier national analyses. We present new findings on the composition of the uninsured in 2020 without reform, the offers of health benefits by employers, and the increase in costs to different payers.
In previous reports, we showed that health care costs, health insurance premiums, and out-of-pocket health spending were likely to continue to grow in the absence of reform. There is evidence of deceleration of cost growth because of the recession, though there have also been reports of substantial premium increases. As the economy improves, there is reason to believe that the cost to employers, individuals, and families will continue to increase at rates similar to those we’ve experienced in recent years. Historically and in long-term projections by the Centers for Medicare and Medicaid Services (CMS), health costs tend to rise two percentage points faster than gross domestic product (GDP).
To the extent health care costs and premiums grow faster than incomes, employers will be less likely to offer coverage and individuals will be less likely to take up coverage when offered. Nongroup coverage will fall as well. Those eligible for Medicaid and CHIP will be more likely to enroll due to increasing premiums and out-of-pocket health care costs in private insurance and declining employer insurance coverage. Continued increases in income inequality will also lead to greater Medicaid enrollment as more people fall below eligibility thresholds.
Greater public program enrollment will increase federal and state spending. The decline in employer-sponsored insurance (ESI) will result in an increase in the number of uninsured. This will mean increases in the amount of uncompensated care (medical care received by the uninsured and not paid for by themselves, including donated care and bad debt) and associated spending by state and local governments for those without coverage.4 The end result is that there are likely to be significant changes in the distribution of health insurance coverage and increases in spending both privately and publicly.
In this paper, we use the Health Insurance Policy Simulation Model (HIPSM) to estimate the likely changes in coverage and health care costs that will occur nationally from 2010 to 2020 in the absence of health insurance coverage reform and measures to restrain cost growth. We make estimates under three alternative scenarios, which vary assumptions about health care costs and premium growth as well as unemployment, income growth, and changes in income inequality for 2015 and 2020.5 We asked the following questions:
1) How many people will have employer-sponsored insurance in 2015 and 2020? What will happen to employer spending on health insurance premiums? To what extent will workers continue to have access to health benefits through their jobs?
2) How many people will obtain coverage under Medicaid given changes in incomes, health care costs, and declines in employer coverage? How much will spending on public insurance (e.g. Medicaid and CHIP) increase?
3) How many people will be uninsured in 2015 and 2020? How will the cost of uncompensated care change over time given changes in the number of uninsured? The Cost of Failure to Enact Health Reform: 2010–2020 4
4) What will the composition of the uninsured look like in ten years compared to now if health reform fails in terms of income, age, and health status?
Data and Methods
HIPSM models the behavior of employers and individuals and their decisions to offer and take up coverage. The model is designed to show the impact of policy changes on firms’ decisions to offer coverage, individuals’ decisions to leave current private coverage and enroll in Medicaid, and decisions by the uninsured to take up new coverage when eligible. The model uses data from several national data sets. It relies primarily on 2004 data from the 2005 Current Population Survey (CPS) Annual Social and Economic Supplement, but data from several other surveys are matched to the CPS. The model includes a detailed simulation of Medicaid eligibility and enrollment, including the most important eligibility rules for each state. In the model, we also adjust for the undercount of Medicaid on the CPS. The behavioral effects in the model are calibrated to findings in the empirical economics literature.6
To obtain a current baseline, we grow the coverage estimates from 2004 to 2008 given actual changes in coverage and population growth between 2004 and 2008 as measured by the CPS. Then to reflect worsening economic conditions between 2008 and 2010 we apply estimates from Holahan and Garrett to estimate the impact of higher unemployment rates on changes in health insurance coverage over that period.7 We use new estimates of health care cost growth from the CMS Office of the Actuary.8 The effects of recent updates are modest, but they limit comparability of these results to results from the earlier papers.
In implementing the growth rate assumptions described below within HIPSM, we use the model to generate behavioral responses to the cumulative amount of health care cost growth, net of income growth, that is assumed to occur between 2010 and 2015 and 2020. This rise in the relative price of health care and health insurance premiums is modeled as a “reform” within the baseline year. As private health insurance premiums rise, coverage becomes less affordable and demand falls. Fewer firms offer coverage and fewer workers take up their ESI offers. Fewer individuals purchase nongroup coverage. Those who are eligible for Medicaid or CHIP become more likely to enroll. More people become uninsured. Given these behavioral responses, we then age the population to 2015 and 2020 by making adjustments to the weights of the observations in the HIPSM output file. The reweighting adjustments take into account the assumptions for changes in employment, incomes, offer rates, and changes in the population by age and gender cells. Further description of the model and methods is presented in Health Reform: The Cost of Failure.9
The Three Alternative Scenarios
We used three alternative scenarios to project changes in health care costs and coverage between 2010 and 2015. These are based on a series of assumptions that are shown in the top panel of Table 1. The worst case assumes that the unemployment rate does not return to full employment levels by 2015, that income growth is slow, and that health care costs will grow somewhat faster than projected by CMS actuaries. We also assume in the worst and intermediate cases that firm offer rates fall—a factor seen in the prior recession, which has the effect of lowering
Table 1: Growth Rate Assumptions Under Each of Three Scenarios, by 5-Year Period
|Unemployment rate at end of period||Employment rate at end of period||Income growth (average annual growth)||CPI
(average annual growth)
|Medicaid health care spending per capita (average annual growth)||Private health spending per capita (average annual growth)||Private premiums (average annual growth)||Out-of-pocket health care costs (average annual growth)||Additional decline in ESI offer rate due to recession|
|2010 to 2015|
|Scenario 1 (Worst):||7.1%||61.2%||1.0%||2.0%||6.0%||7.0%||8.0%||3.5%||Yes|
|Scenario 2 (Intermediate):||6.1||62.0||1.5||2.0||5.0||6.0||7.0||3.0||Yes|
|Scenario 3 (Best):||5.1||62.8||2.0||2.0||4.0||5.0||5.0||2.5||No|
|2015 to 2020|
|Scenario 1 (Worst):||5.1||62.8||1.5||2.0||6.0||7.0||8.0||3.5||No|
|Scenario 2 (Intermediate):||5.1||62.8||2.0||2.0||5.0||6.0||7.0||3.0||No|
|Scenario 3 (Best):||5.1||62.8||2.5||2.0||4.0||5.0||5.0||2.5||No|
|Source: Urban Institute analysis, HIPSM 2010.|
Without significant reform that makes health insurance more accessible and affordable while reducing the rate of health care cost growth over time, the number of uninsured and health care spending would both increase dramatically. The ranks of the uninsured would increasingly be filled with middle-income, higher-income, and older individuals who have coverage now. Medicaid enrollment would increase because of the erosion of private coverage. Costs per enrollee would also increase because of medical care inflation. As a result, the cost of financing public programs would place added burden on taxpayers. The rising cost of caring for a growing number of uninsured persons through safety net programs would also add to taxpayer burdens. Employers would face sharply increasing health care premiums and as a result, many small and medium-sized firms would stop offering coverage. For employers who still offer coverage, these additional costs would be passed onto workers as lower wages over time. In the short-term, business profitability for those who still offer coverage would be adversely affected. Finally, individuals and families would face higher out-of-pocket costs for premiums and health care services, along with higher tax burdens.
We recognize that health reform itself would also be costly. If reforms like those recently passed by the House and Senate are enacted, government expenditures would increase more than they would without reform because of increases in Medicaid eligibility and enrollment and subsidies to low-income people. Increases in Medicaid spending would be tempered because there would be less erosion of private insurance and coverage would be available through the exchanges. Spending on uncompensated care for the uninsured would also fall. The increases in government expenditure would also be affected by the cost containment provisions ultimately enacted. Employer spending would also grow under reform, though it should be lower for small firms who have access to exchanges and tax credits. Comprehensive health reform would stem the continuous erosion in the number of Americans with health care coverage and make coverage more affordable for a large number of lower-income families. Reform would also decrease financial pressures on the hospitals and clinics that provide care to the uninsured, reduce many system inefficiencies, and ultimately improve the health and financial security of Americans. While enacting health reform will be difficult and expensive, the cost of failure is also high and probably unsustainable.
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