The so-called “era of precision medicine” arrived years ago. Genomic analysis is now a mainstay in the treatment of different cancers and the development of new drugs. Sophisticated diagnostics determine if and when an individual is becoming resistant to an existing treatment. Gene therapies are gradually gaining approval as functional cures for monogenic diseases.
It’s an exciting time in medicine, but not all fields have benefitted from the same advances. Oncology programs have proliferated wildly,
becoming an increasingly large share of the clinical drug development pipeline. At the other end of the spectrum, interest and investment in cardiac drug discovery has fluctuated – despite the vast medical need and market opportunity.
Heart disease remains the leading cause of mortality for both men and women in the United States, driving one in every four deaths and annual costs in excess of $200 billion. The burden of cardiac disease is also increasing globally. More than three-quarters of deaths related to cardiovascular diseases (a grouping that includes heart failure, cardiomyopathies, and a range of vascular diseases) now occur in low- and middle-income countries. The enormity of these numbers provides a telling clue as to why these diseases have not been adequately
addressed. For decades, cardiac diseases were classified and treated based on common clinical symptoms that affect millions upon millions of people. Therapies were developed to target these symptoms and not the underlying mechanisms of the disease. More nuanced preclinical disease models were typically cost- and time-prohibitive, with results, often failing to translate to patients. With a lack of novel drugs to treat the underlying cause of heart failure, drugs that treat comorbidities such as high cholesterol and hypertension have remained foundational.
For decades, this has been the norm. Now, a convergence of technology breakthroughs has opened the door to precise molecular targeting and personalization. Some of these developments – such as affordable and scalable genomic sequencing – have benefitted medicine as a whole. Others, such as better preclinical screening models, specifically address bottlenecks related to studying and treating conditions of the heart.
Below we dive into some of these developments with a look at how they are impacting cardiac drug discovery and development and what historical barriers they overcome.
Chronic disease, chronic failure
In an analysis of clinical development success rates from 2006 – 2015, cardiovascular programs (including cardiac- specific programs) had a 6.6% chance of progressing from Phase 1 clinical trials to FDA approval.
The size and complexity of cardiac clinical trials is likely a contributing factor. Diseases that affect >1 million people in the U.S. were three times less likely to gain approval from Phase I compared to non-oncology orphan indications.
Advances in cell biology and 3D models
Cardiac diseases span a range of common and rare conditions, including heart attack, heart failure, arrhythmia, sudden death, cardiomyopathies, and the many diverse genetic diseases of the heart. Coronary heart disease is both a leading cause of hospitalization among adults 65 and over and the leading cause of death in the United States.
There is a strong case for targeting genetically defined cardiac diseases based on their causal mechanisms rather than clinical symptoms. As noted in the BIO report, “Improvements in basic science can enable better success rates. For example, more predictive animal models, earlier toxicology evaluation, biomarker identification, and new targeted delivery technologies may increase future success in the clinic.”
While advances in basic science have fueled the field of oncology, creating relevant preclinical models for cardiac diseases has proven challenging. A cardiac or myocardial biopsy is incredibly invasive and unlike tumors or organs such as the liver, a patient’s heart cells cannot readily be grown in vitro or grafted into a mouse. While these obstacles have hindered the field in the past, they have also encouraged extraordinary innovation – innovation that is now coming to fruition.
The limitations of cardiac animal models
The ancestors of humans and mice diverged approximately 90 million years ago.2 It’s no surprise, then, that research in rodents often doesn’t translate to humans. This is particularly true in certain disease areas, such as cardiac pathophysiology, which have been historically held back by the limitations of various animal models.
Progress has been made in recent years. To recreate heart physiology, newer small animal models (including mice, rats, and guinea pigs) employ various methods from genetic engineering to surgical techniques to pharmacological approaches.3 Despite this, significant gaps remain:
Factoring in lifestyle: Diseases such as heart failure represent a complex mix of genetic and environmental factors. Some people with genetic predispositions may never develop the disease. Others may be impacted earlier in life, partly due to lifestyle factors such as stress, diet, and smoking. These variables all complicate the pathophysiology of cardiac diseases, making them hard to recreate in a single experimental model.
No PDx equivalent: Another disadvantage is the lack of patient-derived xenograft (PDx) models. In oncology, human tumor cells or tissue may be grafted into an immunodeficient or humanized animal model (usually a mouse). As the tumor grows in its new host, it provides researchers with a unique window into human cancer biology, allowing them to track the natural progression of the disease and the impact of various interventions. Heart cells cannot be transplanted in this way, eliminating a valuable and robust research tool.
Mice vs. men: While rodents form the backbone of animal research, they differ greatly from humans when it comes to the anatomy, physiology, and pathology of the heart. Compounding this, their smaller size complicates studies that require imaging, surgical interventions, and blood sample collection. Larger animal models, such as pigs and dogs, address many of these challenges but require far more resources and are thus used sparingly.
While animal studies are valuable, alternative models are needed to create an affordable and scalable method for generating human-relevant cardiac data. There is also a desire across the industry to reduce reliance on animal models from a welfare and research ethics standpoint, in line with the 3Rs (replacement, reduction, and refinement).
Valo’s Biowire II
Having access to reproducible and scalable functioning human heart tissue in the lab allows researchers to ask vital questions and generate the kinds of data that haven’t been readily available in the cardiac space. Nuanced heart conditions are transformed into comprehensible genetically defined diseases. This information guides short-term decisions and can increase the overall probability of drug development success.
Valo models bring to light mutations found in cardiomyocytes. By replicating this nuanced human biology in the laboratory, we can better understand disease. With a blend of biology and engineering, we can investigate how those genetic changes influence chemical signaling and contractility. We can even test the effects of different compounds. All of this helps drug developers anticipate the positive and negative effects of a cardiac therapy.
This quality of data is what drug developers need to move investigational therapies into the clinic, as a treatment for a genetically defined disease – or even for just one person. Along with developing healthy and diseased cardiac models, Valo can also make tissue representative of a specific individual’s heart. This allows scientists and clinicians to understand, experiment, and tailor their care on a case-by-case basis. In other words, BiowireTM II unlocks precision cardiac medicine.
The March Towards Precision Medicine
Tailoring treatments based on certain patient characteristics, such as genetics, confers many benefits, from greater therapeutic efficacy to fewer adverse events and smarter more targeted clinical trial designs. Financially, this approach can also significantly decrease drug development costs and increase the likelihood of regulatory approvals.
One of the central tenets of this precision medicine approach is the use of measurable biological markers (biomarkers) of known significance. Biomarkers can inform all stages of drug development, from enrichment to stratification, patient selection, safety, and efficacy. The challenge in the cardiac space is uncovering human-specific biomarkers as those identified in animal models often don’t translate. This is another area where advanced in vitro models may add value, mirroring human heart physiology in health and disease.
While not used as broadly as in oncology, cardiac biomarkers have been used in various clinical trials. Common examples include CK, CK-MB, cardiac troponin T, troponin I, myoglobin, and cardiac enzymes. While more options could help personalize and de-risk new cardiac medicines.
In 2000, approximately 15% of oncology clinical trials included a biomarker. By 2018, a majority (55%) used at least one, in line with findings across the industry that enrichment of patient enrollment at the molecular level correlates strongly with success.
While precision medicine often focuses on uncovering the genetic determinants of disease, many diseases are also influenced by environmental factors and the relationship between genes and the environment. One of the ways this complexity is being addressed is through the introduction of phenomapping. This approach involves grouping patients based on the manifestation of their disease rather than the disease itself, allowing scientists to target their drugs, devices, and clinical trials more specifically.
Ultimately, biomarkers, phenomapping, and personalized medicine more broadly are all inextricably tied to data science. Of particular value is machine learning, a subset of artificial intelligence (AI) in which computer programs access data and use it to “learn” for themselves.
Machine learning is an increasingly integral part of cardiac science, helping define and diagnose subsets of the disease and expediting the discovery of new drug targets. For example, in one phenomapping study, scientists analyzed a combination of 67 laboratory, electrocardiographic, and echocardiographic markers with machine learning algorithms to find patterns in 397 patients with heart failure with preserved ejection fraction (HFpEF).6 Data of this size and complexity cannot be parsed manually.
A genetically defined alternative
A 2012 startup, MyoKardia, represents the shift towards precision medicine within cardiac drug discovery and development. Instead of approaching heart disease as a broad population, MyoKardia targets the underlying causes of specific cardiac myopathies, identifying subsets of patients who share specific disease characteristics.
In May 2020, the company announced results from its Phase 3 trial of mavacamten for the treatment of patients with symptomatic obstructive hypertrophic cardiomyopathy. Despite being a pivotal trial, it enrolled just 251 participants. Around 50% were randomized to receive a placebo, while 123 received the investigational drug. The study ran for 30 weeks, meeting its primary and secondary endpoints.
Later that same year, Bristol Myers Squibb announced it had acquired MyoKardia for $13.1 billion. Successful cardiac trials and exits will no doubt encourage more innovation and early capital investments in the space.
Expensive trials, incremental benefits
In an analysis of 138 pivotal clinical trials that provided the basis for approval of 59 new therapeutic agents by the FDA from 2015 to 2016, the median estimated cost per trial was found to be $19.0 million. The cardiovascular trials were estimated to be more than eight times more expensive than the others.
The highest estimated trial cost – $346.8 million – was
for a noninferiority trial that assessed the efficacy for hospitalization and cardiovascular mortality of a new combination drug for chronic heart failure, sacubitril- valsartan. The trial enrolled 8,442 patients with an aim to demonstrate noninferiority to enalapril, a proven agent in this patient population.
“Drugs are more expensive to test when they have smaller effects that require observing more patients for longer periods of time,” study author Thomas J. Moore told CardiovascularBusiness.com. “This applies to many cardiovascular drugs because they have to be shown non-inferior to drugs we already have, or because they are intended to reduce risk of future events, such as strokes or heart attacks, that may occur rarely. In contrast, an effective new antibiotic could potentially benefit every treated patient in a few weeks’ time.”
Looking ahead: The future of precision cardiovascular medicine
The shift back into the cardiac research space is happening quickly for several reasons. First and foremost, the need remains: Millions of Americans and tens of millions more worldwide are at risk for or suffering from, potentially fatal heart diseases. We also have a backlog of known targets that are ripe for investigation.
On the financial front, emerging companies are gaining traction and recognition for their ability to define and segment subsets within cardiac diseases. In 2020 alone, Verve Therapeutics raised $63 million in a Series A2 financing round to further its gene-editing therapies for heart disease. A small startup, Novo Bioscience, raised $4 million to advance its preclinical regenerative medicine program, which aims to repair and restore damaged heart muscle tissue. Prior to acquisition, Valo’s TARA Biosystems closed on a $10 million Series A2 financing round. Groups like Bridge Bio are investing eagerly, and large biopharma companies – like Bristol Myers Squibb – are acquiring established programs in early, mid-and late-stage clinical trials.
Ushering in a new era of cardiac precision medicine will require an interdisciplinary effort. Experts from data science, molecular biology, genomics, cell, and tissue engineering, and more, will all be involved from drug discovery through clinical trials and commercialization. Those experts are now coming together to maximize new tools and available capital.
In this way, Valo’s stem cell and tissue engineering platform stands on the shoulders of giants, building upon the diverse technology revolutions outlined above and taking it one step further. It addresses one of the major remaining bottlenecks in cardiac drug development: the ability to translate research findings into the clinic.
Precision cardiac medicine won’t happen overnight, but the barriers have fallen. That goal is now within reach.