This blog was written by Vanessa King, CEO of Luc Therapeutics, as part of the From The Trenches feature of LifeSciVC
Almost 15 years ago – in 2003, to be precise – I was working with genome sequencing pioneer Craig Venter. A dream job for a Ph.D. molecular geneticist. Together, we were building the Venter Institute’s projects that – a decade later – evolved into Human Longevity and Synthetic Genomics (the former of which’s recent $220 million Series B should surely be the topic of a future blog). Separate from all of that high science, however, it was the Wall Street Journal that sounded the siren’s call to return to drug discovery. A call which has led me to an area now at the frontier of how we discover drugs and treat patients.
As a Ph.D. molecular geneticist, I’d always been drawn to creating cures for patients. But conversations while considering medical school and then while working in strategy consulting for large pharma had convinced me that the future was clearly not now, back then. It was clear that medicine was being practiced – and that drug discovery was being done – in ways that were far from a mechanism-based understanding of sickness and health.
But, on the treadmill that April morning, reading (a, in those days, paper copy of) Sharon Begley’s now famous (or it should be) piece, “Physician Researchers Needed to get Cures out of Rat’s Cage,” I realized that I had to enter the arena.
Her piece engagingly pointed out the disconnect between treating disease in animals and in humans, “lab mice … have responded quite well to an experimental Alzheimer’s vaccine … lab rats with paralyzing spinal cord injuries have walked again, albeit awkwardly, after treatments. And, we’ve cured cancer in enough rodents to fill several New York subway systems.”
But, in many ways, her piece heralded an end to that era. Or, at least the beginning of that end. In the last couple of decades, high throughput sequencing has enabled changes in the efficiency and productivity of discovery efforts across almost every therapeutic area, through an increased focus on interrogating the genetic basis of disease in healthy and diseased humans and model systems and enabling the implementation of other nucleic acid-based tools. And, that same technology has helped evolve disease treatment paradigms, as well – most notably in oncology – where treatment regimens can be tailored to the specific nature of patients’ cancers. As an amusing side note, Dan Vasella’s “Magic Cancer Bullet” was also published in 2003 – heralding the arrival of cancer drugs tailored to specific genetic perturbations.
Today, exciting developments in different modalities, e.g., next generation immunotherapies, gene-editing, etc. continue to bear much promise for improving biotechs’ and pharmas’ abilities to bring ever-better treatments to patients.
When we talk about “era-changing” – about enabling us to move beyond curing rats – we have a stealth entry I’d like to highlight: EEG – electroencephalogram. EEG measures electrical activity in the brain. Importantly, the patients that will benefit most from EEG are those arguably least effectively served by therapeutics today – patients with psychiatric disease.
In short, EEG is part of the reason why the answer to the question posed by Adam Rosenberg in another recent From the Trenches Blog “Are We Poised for a Neuroscience Research Renaissance?” is a resounding yes.
For background before delving back into EEG – across most diseases, patients and clinicians are able to get some physiological understanding of the details of a patient’s disease to aid diagnosis and before initiating treatment: cholesterol levels, electrocardiograms, or even the location and size of a tumor. But, in psychiatric disease, behavioral observation and patient interviews have been the currency of diagnosis: patient interviews interpreted by clinicians based on DSM criteria, descriptions of the symptomology of different conditions (specifically, we’re talking about the Diagnostic and Statistical Manual of Mental Disorders, published by the American Psychiatric Association, the most recent version of which was 2013’s DSM-5). Note that there are whole camps pro- and anti- the DSM. Generally acknowledged now as a tool useful for diagnosis and treatment, but not for fundamentally advancing our understanding of the pathophysiology of psychiatric conditions (for a thoughtful and brief summary, see former NIMH Head Thomas Insel’s blog, and his and Bruce Cuthbert’s longer article Toward the future of psychiatric diagnosis)
For anyone who has lived first-hand the process of diagnosis for psychiatric disease, it is an often-frustrating and confusing journey. For patients with some diseases of the brain, this soon may change. EEG is a tool that is poised to unlock our understanding of dysfunction in the brain’s circuitry in patients with some psychiatric diseases. And, that understanding, when paired with new treatments, holds the promise of better lives for these patients.
The controversy around DSM actually helped enable EEG’s rise in utility. So did clinicians’ frustration with DSM’s focus on phenomenology rather than neurobiology. And, also I suspect, pharma companies’ much-described exodus from psychiatric disease drug discovery, thanks in large part to a lack of tools to cut through the heterogeneity of patient populations in these therapeutic indications.
The need for us to better understand the psychopathology of these diseases really is all about the patients. Despite the drugs currently on the market, the need for new and better therapeutics to restore normal function and improve quality of life is striking.
Schizophrenia, the focus of our company Luc Therapeutics, is a good example. When it was first labelled by Western medicine, schizophrenia was called ‘dementia praecox’– premature dementia. This recognizes that a global cognitive impairment characterizes the disease. In fact, patients are one-to-two standard deviations less functional than healthy controls on every measure of cognition. Yet, today, all of the therapeutics used to treat schizophrenic patients target the condition’s psychosis, and do not improve the cognitive disability.
But I digress. Let’s return to why EEG is revolutionizing drug discovery in psychiatry and how that will translate into better cures for patients.
In 2009, the National Institute for Mental Health introduced a new framework for research on psychopathology, RDoC – the Research Domain Criteria. While the term itself is opaque, the revolution it has launched is quite the opposite. In contrast to research based solely on current diagnostic categories as defined by DSM’s symptomology, RDoCs ensures that researchers integrate data from areas such as genetics, physiology, and cortical function in order to better define the cognitive and biological bases of individual patients’ diseases.
I have to caveat my use of the word ‘revolution’ by saying that we’re still in early days of this new research paradigm. And, few if any of its findings have been translated into every day clinical care. But the revolution is here.
For a short, readable review see Insel and Cuthbert’s piece in Science in 2015 and for a cool example of researchers trying to analyze differences in patients’ neurobiology to define meaningful subgroups that would have been missed by examining clinical phenomenology alone see Clementz, et al.,’s 2015 article “Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers” in the American Journal of Psychiatry.
We are living this revolution at Luc, thanks to the work of researchers who’ve started to investigate the differences between how normal individuals and schizophrenic patients process the world — specifically, electrophysiological differences in the function of the cortex.
So, why is this ‘living the revolution?’
Our focus at Luc is on discovery of new therapeutics to improve cognition in patients with schizophrenia. And, now, thanks to EEG…
- We have an easily-measured, quantitative biomarker for what we want to modulate in patients. In particular, we’ll be able to use an EEG-based measurement called Mis-Match Negativity (MMN) which is a measure of how the cortex processes auditory signals. MMN has been evaluated in large, multi-center studies. Thanks to those studies, MMN has been demonstrated to be a robust biomarker that differentiates the brains of schizophrenic patients from healthy volunteers. Furthermore, the MMN data was collected by non-specialists, making a compelling case for the potential utility of this biomarker in real world clinical trial settings
- We can – early in the discovery process – assess whether our compounds affect cortical function the way we want them to. We’ll be able to do this because MMN has been successfully back-translated to animal models. Previously, discovery scientists had to conduct their in vivo pharmacology in behavioral models – e.g., seeing how fast a mouse swims after being dropped in cold water – and extrapolate from that to likely impact on the brains of patients. Now, in contrast, rodent brains can model human ones purely through the conserved architecture and function of the neural circuits that compose them. For interesting review see 2016’s Harms, Michie and Näätänen’s Psychology.
Hence, the revolution.
As clinicians move swiftly towards being able to diagnose patients’ individual neuro-pathophysiologies – yes, folks are already talking about using EEG as part of the diagnostic process for patients with schizophrenia (see Light and Swerdlow’s Future clinical uses of neurphysiological biomarkers to predict and monitor treatment response for schizophrenia), we who labor to discover therapeutics for those patients finally have tools worthy of the challenge.
Of course, a tool is nothing without the experience to wield it effectively. And, the vision – grounded and practical, and “non-purist” enough — to push it to its true utility. More on these topics in future blogs!
