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The Challenge and Promise of the Genomic Era--Presidential Address of George Sledge, MD

Jun 02, 2011

Watch a video of Dr. Sledge delivering his speech or read the full transcript below.


Welcome, colleagues, to the 47th Annual Meeting of the American Society of Clinical Oncology. Thank you all for attending—and for the passion and intelligence you bring to our society. It has been my great honor to serve as your president this past year, a year of momentous change not only for ASCO, but for health care and for cancer biology as well. It is a time of real progress in the science of cancer, and I would like to spend some time with you today sharing my thoughts on where the emerging science of cancer is taking us as a profession.

I am dedicating this talk to my administrative assistant, Lisa Miller, who is here with us today. Lisa keeps me out of trouble; she is dedicated, cheerful, kind and smart. She is a wife and the mother of two beautiful daughters. Lisa also harbors a BRCA1 mutation. Recently, she was diagnosed with a triple negative breast cancer and is currently receiving chemotherapy. She is one of over a million and a half Americans who will be diagnosed with cancer this year.

I know that you will share my best wishes for Lisa, and thank her for her willingness to represent those fighting their own personal battles with this disease.

The other person who keeps me out of trouble is my wife, Carolyn. She and our three sons, Daniel, Matthew and David, have been a great source of support—and pride—throughout my career. My love and thanks to you all.

[By the way, there is no truth to the rumor that Carolyn called the police to report a strange man in her house when I came home from an ASCO trip last week.]

ASCO Presidents benefit greatly from the support of ASCO volunteers. This year, I drew on a hugely talented group of members populating our many committees. I do not have time to name them all, but I draw your attention to Doctors Kathy Miller and Chuck Blanke, Chairs of the Scientific Program and Education Committees. They have devoted their all to making this meeting a success, and I am grateful to them. Thank you, Kathy and Chuck. I hope we are still friends after all I’ve put you through.

ASCO also benefits from an incredibly talented staff. Their esprit de corps, their work ethic, and their intelligence are incredible. From our CEO Allen Lichter on down, I have never worked with such an impressive staff in any organization. They go out of their way every day in support of our mission. Thank you, guys.

And now a brief update on the state of ASCO—and of cancer care. We are over 30,000 strong, some of whom join us today for the first time. Welcome to our new colleagues. We draw real strength from the diversity of our membership. We are an American society with an international flavor, with members in 121 countries. We are a society of surgical oncologists, of radiation oncologists, of adult medical oncologists and pediatric oncologists, of gynecologic oncologists and hematologists and all of the affiliated members of the cancer care team.

We practice in hospitals and clinics; we serve in the community, in academia, in government and in industry. We are the world’s cancer doctors. We are the front line in the battle against an ancient scourge. We bring new therapies to the clinic. We advance the science of cancer medicine, even as we care for our patients. We stand up on behalf of our patients, present and future.

We are the American Society of Clinical Oncology.

One of the more important things we do is to foster the next generation of cancer researchers, through the Conquer Cancer Foundation’s Career Development and Young Investigator Awards. This year we will give out 8 CDA and 47 YIA Awards. There are many more deserving candidates we cannot fund.

You can help us create opportunity through the Leadership to Legacy program of the Conquer Cancer Foundation. YIA’s and CDA’s are the seed corn for the next generation of clinical and translational cancer researchers. Your support can kick-start the career of a young investigator, perhaps one sitting in the audience today wondering whether he or she will make it as a cancer researcher. So please support our Leadership to Legacy program.

What of the state of cancer care? First, the good news: cancer death rates are falling in the United States through the application of modern science to the clinic. We owe this in part to the receding tide of cigarette-induced malignancy, partly to the application of better diagnostics, and of course new systemic treatments to the cancer problem. We have much to be proud of; but we have much yet to do. We still lose far too many patients to a premature death—over half a million this year in the U.S. alone.

At the same time we face real challenges. The first of these is a rising tide of cancer related to an aging population. This is an international problem: by 2030 cancer deaths worldwide will exceed 11 million per year.

Largely because of these demographic changes, there will be a steadily increasing call on our services. The rapid increase in therapeutic options for cancer patients will also push demand. We are—I regret to say—the one sure growth industry.

In fact, the changing demographics of cancer, combined with a relative lack of increase in those providing care, means that demand for cancer care will soon far outstrip the supply of oncologists. How will we care for our patients? What innovative means can we develop—and develop soon—for the need is pressing? These workforce challenges will increasingly dominate our society’s thoughts and efforts.

We also face growing economic challenges. The cost of healthcare outpaces inflation, and is the major cause of arguments over healthcare. But the cost of cancer care, and in particular the cost of cancer drugs, has soared in the past decade. And a recent analysis, published by Mariotto and colleagues in the JNCI, has suggested that by 2020, costs will increase another 27-39%. This is based solely on the changing demography of cancer in the U.S. and will occur even if no new drugs are approved. These trends are not sustainable.

Though doctors providing care are not responsible for the cost of these drugs, we are responsible for their appropriate use. We witness the effects of these costs on our patients, and we will be a target for many wishing to control health care costs.

What about new therapies? The clinical trials workforce is dwindling in the United States. Overall, there has been an annual 3.5% decline in US-based investigators since 2001—even as there has been an absolute and proportional increase in investigators based outside of the US. We welcome an international increase in clinical trialists, but a steady decline in the US clinical trials workforce is real cause for concern. Clinical trialists are the bridge linking laboratory vision to patient care.

Being a clinical trialist is hard work; it is poorly compensated; it has been for some time a labor of love. Labors of love can be derailed by abusive relationships with unsupportive partners.

The challenges to participation in research trials are many, as outlined in a 2010 report issued by the Institute of Medicine. The pace of clinical cancer research is threatened even as scientific knowledge continues to explode. These are largely self-inflicted wounds, human in cause and therefore amenable to human solution, given sufficient resources and political will.

At the same time, the success rate for Phase III trials in oncology remains abysmally low: we are just not good at picking winners compared to every other medical specialty. Why this is the case is undoubtedly complicated. I suspect that many of the failures have their roots in our incomplete understanding of tumor biology and the imperfect lessons we receive from early stage trials, where the signal to noise ratio is low.

None of these challenges are news to this audience. You live with them every day. But I would like to suggest to you that we face a new challenge, a challenge full of promise: this is the challenge of the genomic era.

In calling this the genomic era, I am well aware that genomics is accompanied by transcriptomics, proteomics, metabolomics, epiegnomics, pharmacogenomics and no doubt ten other “omics”; but let genomics stand as the surrogate marker for the tsunami of scientific knowledge bearing down on us.

Cancer therapy has gone through several different but overlapping eras. The oldest, beginning in the 19th century, was an era of local-regional therapy. Nonspecific systemic therapies came to the fore starting in the late 1940’s and early 1950’s, followed by targeted therapeutics. Targeted therapeutics exploded in the past decade, as the fruits of laboratory studies of cancer biology were translated to the clinic. We are now, I would suggest, just beginning to enter a 4th era, the era of genome-based therapy.

The era of targeted therapy is shown here. Most of these have only been attacked with therapeutic intent in the past decade. This is an ongoing revolution based on a simple yet powerful principle: find the driver of growth for a cancer in the laboratory; measure it in the clinic; then attack it with a specific targeted therapy—typically an antibody directed against a receptor or a small molecule hitting an internal kinase pocket.

Any rational person would hesitate to suggest that the era of targeted therapy—which is represented in our plenary session and in many oral presentations at this meeting—is over. We continue to find and treat novel targets, and treatments for several of these targets continue to evolve with the promise of increasing success. So why do I suggest that we are moving into a new era, a genomic era?

The first two human genomes were decoded in 2001, at the cost of over 3 billion dollars. The first complete sequencing of human cancer genomes was published less than three years ago. As recently as this last year, the deep sequencing of a single patient’s cancer was enough to get a paper published in the journal Nature. Today, as a result of efforts such as the NIH’s Cancer Genome Atlas Project and the International Cancer Genome Consortium, several thousands of cancers covering 20 major tumor types are being sequenced.

Such large-scale sequencing will rapidly change our understanding of cancer biology; it will identify new targets in previously hard to treat diseases; and it will explain the causes of drug resistance. Within the next few years, perhaps by the end of this decade, we will likely see the beginning of population-based deep sequencing of patient’s tumor genomes.

In addition to tumor genomics, genomic analyses of the host proceed apace. Genome-Wide Association Studies involving large swatches of the human genome are now becoming routine. Such studies will provide valuable insights into variations in drug response and toxicity. For instance, my colleague Bryan Schneider today will report the results of a GWAS study at a Clinical Science Symposium devoted to host genomics, implicating a previously unrecognized genetic source of variation in taxane-induced peripheral neuropathy.

Host genomics, combined with tumor genomics, will represent the basis for an individualized understanding of risk and benefit in the not-too-distant future.

Underlying these developments is the rapid fall in the price of whole genome sequencing. Indeed, the fall in the cost of sequencing is occurring at a more rapid rate than the regular fall in the cost of microprocessors, known as Moore’s Law. We are on the verge of what specialists in the field refer to as the $1000 genome, the cost point at which personalized genomics becomes possible.

So what happens when, a few years from now, a patient walks into a doctor’s office and hands a physician a memory stick loaded with gigabytes of personal genomic data?

Lest you think this prospect ridiculous, bear in mind that if you are willing to pay for it you can already get your host whole genome sequenced and delivered to you on a USB drive, albeit at a still substantial price. Tumor genomes will not be far behind, though it will be several years before we have appropriate analytical tools available for everyday practice. But have no doubts, the genomic era is headed our way.

When data are that cheap, every patient’s cancer will be informative for tumor biology. And things will get very, very complicated. We will actually be able to measure the degree and kind of mutations in an individual’s tumor. This “In Your Face” Genomic analysis will profoundly affect our understanding of etiology, prognosis and therapy for cancer patients.

The promise of this era is revealed by a recent paper in JAMA, in which deep sequencing of a patient’s leukemic cells revealed a previously cryptic fusion oncogene amenable to therapy with a retinoic acid receptor inhibitor. This is the very first case, to my knowledge, of whole genome sequencing leading to individualized therapy in cancer, but it will certainly not be the last. We can look forward to a future in which the unraveling of the secrets of the genetic code is commonplace, expected, and routinely drives care. But this case, as wonderful as it is as a harbinger of our collective future, is not the whole story. Not every story will end this happily.

“Stupid cancers” and “smart cancers”

My sense of the past decade is that human cancers are segregating out based on the number of mutational drivers of growth, invasion, and metastasis.

Let’s call them “stupid cancers” and “smart cancers”; an oversimplification that serves to identify two ends of a spectrum.

“Stupid cancers” have a single dominant mutation and a small mutational load.

Targeting that dominant driver is regularly effective, and resistance is rare, often occurs late, and can frequently be reversed via other attacks on the same pathway.

Smart tumors have multiple simultaneous drivers, carry a large mutational load, and require the targeting of multiple drivers. Resistance is common in smart cancers and occurs early into treatment.

In the era of targeted therapy we have focused on specific mutational events: BCR/ABL, c-Kit, HER2, JAK, BRAF and others.

But the new currency of the genomic era, layered on top of our prized single driver mutations, is mutational load, measured in mutations per megabase.

I thank Gaddy Getz of the Broad Institute for allowing me to share this data with you.

Looking at >1000 whole exomes from various tumor types, we see that mutation rates can vary by more than a 1000 fold.

Several hematologic and childhood tumor types are at the low end with less than 1 mutation /Mb; head and neck cancers, colorectal cancer, lung adenocarcinoma and squamous cell cancers and finally melanoma have a median close to 10 mutations/Mb and can reach 100 mutations /Mb.

How does this play out in the clinic? The prototypical “stupid” cancer is CML. This once highly lethal disease is driven by a single chromosomal translocation. Targeting the product of that BCR-ABL translocation resulted in a high response rate and long survival times with imatinib, the very first drug to come along. And if that drug fails, juts use another “ib” targeting the same kinase domain. I do not mean to denigrate either the groundbreaking research that led to imatinib or the use of these drugs: this is a true victory for targeted therapy and demonstrates its very real promise for cancer patients. But this is a stupid cancer.

In contrast, look at cigarette-induced non small cell lung cancer. The first lung cancer genomes were published last year. To look at the Circos plot on the upper left gives you some sense of the challenge we face in this disease. In Circos plots, the chromosomes are arrayed in a circle. In the innermost ring we see multiple inter- and intra-chromosomal rearrangements, either as long red lines crossing between chromosomes or short blue intrachromosomal loops. In the next ring, we see frequent loss of heterozygosity, followed by many copy number variations in the next ring and finally single nucleotide variants on the outside ring.

If we look now at the EGFR pathway from this patient, on the lower right, we see multiple points of amplification, loss of heterozygosity, and mutation—all within a single pathway. Because the investigators could count the number of mutations—and knew the patient’s smoking history—they were able to determine that the patient’s tumor had one mutation for every three cigarettes smoked. This is a “smart” cancer.

It is no surprise that NSCLC has been resistant to so many different drugs. Indeed, it is surprising that any respond for any prolonged length of time. Similarly, it is no surprise that the targeted therapies such as EGFR and ALK inhibitors that work best in this disease work preferentially in nonsmokers, who carry a lower mutational load.

Remember last year’s plenary session with the ALK inhibitor crizotinib? Three-quarters of ALK positive patients were never-smokers, and almost all of the rest ex-smokers. Do you want to respond well to a targeted therapy? The lesson seems to be that you need a single dominant driving mutation in a less-mutagenized cancer.

Or consider melanoma. At this meeting’s plenary session we will see a genuine and exciting advance in melanoma therapy related to BRAF inhibition, another important victory in the era of targeted therapy. But BRAF inhibition, as this horrifying picture from a recent JCO publication suggests, will be hampered by the rapid emergence of resistance in some patients.

Indeed, even before the first presentation of the Phase III trial of BRAF inhibition in melanoma, genomic analyses of tumors from patients undergoing BRAF-targeted therapy have revealed at least six separate forms of drug resistance.

Bear in mind that in the coming genomic era, such genomic chaos will be thrust in your face at a very early point. The challenge will to be to use our new knowledge to defeat a smart and treacherous foe.

And, of course, the genomic era is telling us what we already suspected: these tumors evolve, as this study of the primary and metastatic tumors of a pancreatic cancer patient suggest.

As the Circos plot in the upper left shows, some genetic lesions are seen in all metastases, some are partially shared, and some are private to the index metastasis, in this case the crucial KRAS amplicon on chromosome 12. In the upper right, looking at a panel of metastases from one patient, one can see that out-of-frame deletions of different types are found in different clusters of metastases.

This leads to a model of an evolving tumor, even before therapy is administered, in which a primary tumor gives rise to metastases that in turn give rise to genetically different secondary metastases. Genomic instability can defeat our best efforts in smart tumors.

The implications of genomic chaos go far beyond its impact on individual patients. Let’s look at what happens in a clinical trial. Matt Ellis and his ACOSOG colleagues presented a wonderful study at the recent AACR meetings.

Fifty breast cancer patients receiving preoperative hormonal therapy underwent baseline biopsies for Ki67 testing and deep genomic sequencing. Ki67, a marker of proliferation, identifies patients as responders or non-responders, based on prior trial results in the preoperative setting.

Ki67 cuts this population into two equally sized groups. The first thing to notice is that responding tumors harbor, on average, half as many coding mutations as non-responders. Again, this suggests that in the genomic era smart cancers are smart at least in part for quantitative reasons: mutational load rules in the clinic.

But the real surprise is the sheer number of significantly mutated genes—and how many of these mutations occur at frequencies < 5%. Once we get past some of the high-flying usual suspects, like PI3Kinase and p53, everything becomes a rare mutation, and suddenly we are dealing with a whole series of orphan diseases.

And that is only the beginning. Evolutionary biologists have a phrase, the “Red Queen Principle,” derived from Lewis Carol’s Through the Looking Glass, to describe the arms race between co-evolving species. Think of targeted therapies and smart tumors as being part of an evolutionary arms race. When dealing with smart tumors—where genomic instability constantly increases mutational load—are we doomed, like the Red Queen, to run faster and faster just to stay in the same place?

Well, perhaps, if we treat these targets one at a time. But as Jayne Stommel of the NCI has shown in the setting of glioma, while most smart tumors have multiple kinases activated, we can optimize cell kill by inhibiting all of them at the same time.

The implications of these examples for individual patients with cancer are fairly obvious. Genomic chaos forms the basis for the “smart tumors” that cause so much harm. This is as much a quantitative as a qualitative problem. These tumors aren’t hard targets because we haven’t found a single “magic bullet.” There will be no “magic bullet” for these tumors because they don’t have a single driving mutation: we need to think in terms of a “magic shotgun,” loaded with pellets aimed at multiple targets in multiple pathways.

So, let’s assume—because it is probably true more often than we would wish—that cancers have multiple drivers, and that to cure a cancer—and let us use the word cure, for our patients deserve no less—that targeting them simultaneously increases benefit. So now imagine cancers with two drivers, requiring two different kinase inhibitors. What is the number of patients we need to study the combination of two new kinase inhibitors?

I’d like to introduce a new concept, which I call “number needed to study,” something different than number needed to screen or number needed to treat, though the math is similar.

To predict how many patients we need to screen for every patient we study in a clinical trial, we would need to know the fraction of patients who are biomarker-positive for a particular kinase target, and therefore candidates for our targeted therapy. Assays are never perfect, so we need to have a fudge factor taking this into account. Only a fraction of patients are trial-eligible, and not all of them will give their informed consent.

Imagine you are attacking HER2 for the first time. I’ve made these numbers up, so feel free to criticize, but you probably had to screen around 14 metastatic breast cancer patients for each one who eventually entered the clinical trial. It might be worse—I left out some other fudge factors.

Now imagine we perform the same exercise with two kinases, one occurring in a quarter of metastatic patients and the other in 8% of patients. Assume the diagnostic tests are 90% accurate, half of patients are trial-eligible, and 80% of those give their informed consent. If we are dealing with a two-drug combination the number needed to study is 154. Who in their right mind would screen 154 patients to enter one on a clinical trial? And forget three-drug combinations of novel agents.

Are there other approaches than the targeting of kinase networks, which as I have suggested may face daunting challenges? Of course. To name just a few:

We can increase our efforts at cancer prevention; you will recall that the most heavily mutagenized cancers—melanoma and lung cancer—represent self-inflicted wounds.

We can harness the body’s immune system; our plenary session includes one such example.

We can redouble our efforts to interfere with DNA damage repair mechanisms.

We can interfere with the tumor microenvironment.

And we can invoke metastasis suppressor gene products.

We can attack tumor stem cells.

What happens to clinical trials in the era of genome-driven therapy? For those interested in developing agents targeting specific pathways or networks, the task is a daunting one for smart cancers. We will be faced with large numbers needed to study, as I have suggested.

What happens when the next ten patients you see require eight different combinations based on their tumor genomes? Our current system is not designed to handle genomic chaos. It emphasizes single agent trials. It virtually never employs multiple biomarker-driven studies—and biomarkers will be required to validate the genomics. In most studies, biomarker development and analysis are of secondary importance at best. Finally, we have a regulatory apparatus that is ill-suited to the emerging biologic reality.

Meeting the challenges as a profession

How will we meet the challenges of the genomic era as a profession? Will we be passive recipients of, or active participants in, this scientific revolution? I would suggest that we must work to meet the challenges of this new genomic era. We need a trained and motivated workforce. We need a vibrant clinical trials system. And we need to pioneer a rapid learning system for oncology.

Let me touch on each of these points briefly.

I have already mentioned the challenges facing this workforce, challenges each of you is aware of. We will need a workforce that understands the principles underlying the genomic revolution—and an environment that supports the difficult work we do. And we need adequate numbers to face the rising volume of cancer patients and new agents headed our way.

In particular, we need, both in our training and in our clinical practices, to redefine what it means to be an oncologist. If oncology is the study of cancer biology, then the definition of the oncologist of the future must be a clinical cancer biologist.

We will need a vibrant clinical trials system.

ASCO supports the full implementation of the recent IOM report’s recommendations on the Cooperative Groups, with increased efficiencies resulting from functional reorganization of the federal clinical trials system—as well as the resources appropriate to the tasks required by those trials.

The genomic revolution will place special emphasis on the incorporation of translational science endpoints, increasingly derived from whole genome sequencing of individual patient’s tumors, in every trial.

This is currently just a dream, but the falling price of genomics should make this a reality in the not-too-distant future, and it is not too early be planning the first generation of whole-genome-based trials, as Matt Ellis and his ACOSOG colleagues have shown us. Some in this audience may wonder if the cooperative groups have a future in the genomic era. I would suggest to you that the genomic era will require the reinvigoration of the cooperative groups to succeed.

We have Next-Gen sequencing. We need a “Next-Gen” clinical trials system, based on personal genomics, with real-time bioinformatics. The Number Needed to Study problem suggests a need for extensive health information technology systems linking clinical researchers, drug developers, tissue banks and laboratory scientists—and linking them worldwide.

If we are to attack multiple targets simultaneously, we need investigators at many centers testing multiple combinations, those combinations to be derived from genomic analysis of the primary or metastatic tumors of individual patients. Underlying this is a need for greater collaboration, particularly among companies developing new agents. We need new clinical trials designs that allow the simultaneous study of multiple combinations. This will also require redesign of the informed consent process and of our regulatory apparatus.

None of this is easy, but all of it is necessary.

What will be the role of our professional society in this new era? If the health system for oncology is to succeed, all its parts must be healthy and connected. We can begin to make this a reality by committing to a concept called the Rapid Learning System. Described by Lynn Etheredge and advanced by the Institute of Medicine, a rapid learning health system leverages information technology to bring real time innovation to both science and practice. By bringing our communities closer—by linking research to practice—by connecting through technology as well as patient-focused human interaction—we can achieve an international system that will bring us to greater insight to this disease and better care for our patients.

As an organization we view this Rapid Learning System as having three important elements: Health information technology, guidelines, and performance measurement.

Health information technology will be central to the Rapid Learning System in the genomic era. Doctors will need real-time access to clinical data from all practice settings. This in turn will require interoperable databases using common terminology.

Health information technology should offer on-the-spot decision support to oncologists and patients facing the increasingly complex tapestry revealed by modern genomics. It should provide individualized, ready access to a clinical trials systems. It should support appropriate coverage and reimbursement for services. And it should aggregate data so that we can learn from every patient’s experience.

There are real challenges facing us here, challenges involving cost, patient privacy, data ownership, and the dysfunctional silo mentality of health care systems across the globe.

ASCO is not an electronic health records company, but we do believe we have an important organizing role to play in creating the HIT systems of the genomic era.

Our approach to guidelines will also need to change in the genomic era. Guidelines will need to retain their intellectual rigor, but at the same time be flexible enough to deal with the hundreds—or thousands—of orphan diseases revealed by modern biology. They will need to be easily accessible, user-friendly, and add value to daily patient care. Clinical guidance across the full spectrum of cancer prevention, treatment and survivorship should, of course, form the basis for intelligent decision support for doctors and patients. The melanoma treatment finder launched by ASCO and Collabrx this year is a good example. These are challenges that no current guidelines group has yet addressed. ASCO and its volunteers are the right agents of change for guidelines in the genomic era, but we are also happy to work with other guideline organizations on this challenging task.

The Rapid Learning System for Oncology will also require the development of quality measures. We need measures that are attached to a practice’s electronic health records, seamlessly extracting information. These measures should be shared with patients, providers and researchers. They should be endorsed, when applicable, by national standard setting organizations. Their use should support physician accreditation and decision making and be part of an iterative feedback process.

ASCO’s QOPI guidelines are a first step in this direction, but only a first step: much work remains.

ASCO is the right organization to take on this task. Physicians should judge physicians using a meaningful and agreed upon set of patient-focused quality measures. Creating a unified set of measures and standards for our profession is far superior to having a legion of measures imposed on us by a multitude of dueling sources, something that is increasingly—and alarmingly—the case.

This painting by Goya is entitled “Self-Portrait with Dr. Arrieta.” Though nearly two centuries old, and with nary a PET scan in sight, we have no trouble identifying this as a physician caring for a suffering patient. The words at the bottom of this portrait read in translation: “Goya gives thanks to his friend Arrieta: for the skill and care with which he saved his life during his acute and dangerous illness.” Skill, and care.

As we go forward in the Genomic Era, we must be willing to look back. Back to the humane standards that have forever guided our profession. Back to our belief that patients always come first. Back to the realization that the pathways forward all flow from that which is best in the human spirit: our thirst for useful knowledge, our compassion for our fellow beings, and our belief in their essential dignity. From our skill and care.

Thank you for attending the 2011 Annual Meeting. Thank you for hearing me out. Most of all, thank you for the skill and care you provide your patients, your love for your profession, and your devotion to advancing the science of cancer care.

My deepest appreciation to Lisa Miller and all of the other cancer patients in the audience today: you give our lives purpose and meaning.

I leave you with this meeting’s theme:

Patients, Pathways, Progress: Progress to a brighter future, if we will only grasp it.

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