Cancer is a significant public health problem globally. The CDC states that cancer is the second leading cause of death in the United States, closely behind heart disease.
In the past decade, there have been many breakthroughs in cancer treatment. The most notable discoveries are immunotherapy and targeted therapy which have helped patients with certain types of cancer to live longer lives.
However, these treatments come with substantial challenges, including the high cost of drugs and availability and side effects that can be debilitating for the patient.
We will discuss these topics in detail in this blog post to provide you with the most up-to-date information on the latest cancer treatments in development.
Treatment Breakthroughs from 2010 – 2020
In the past ten years, 27% of all new drug approvals were cancer drugs. The majority of these treatment options are immunotherapy and targeted cancer treatments.
There have also been breakthroughs in diagnostic tools, as well as other areas of cancer research.
Let’s take a look at the cancer drugs approved in the last decade in detail.
Immunotherapy is a type of treatment that involves using the body’s immune system to fight off cancer cells. Even though the concept of immunotherapy has been around since the 19th century, it wasn’t until the late 20th and early 21st century that scientists developed techniques to use it as a treatment.
The first patented immunotherapy drug was FDA approved for the market in 2010 – it was a therapeutic cancer vaccine, called Provenge (sipuleucel-T), for advanced prostate cancer. A year later, the drug Yervoy (ipilimumab) was approved to treat metastatic melanoma and was the first FDA-approved immunotherapy drug to be used alone in cancer treatment, rather than in combination with chemotherapy.
Immune checkpoint inhibitors are a relatively new type of immunotherapy. Immune checkpoints are a normal part of the immune system. They prevent the immune system from attacking healthy cells in the body. When special immune checkpoint proteins on T cells (immune cells) recognize and bind to partner proteins on other cells, such as some tumor cells, they send an “off” signal that prevents the immune system from destroying cancer.
Immune checkpoint inhibitors block these checkpoint proteins from binding with partner proteins. This allows the T cells to kill cancer cells through disabling the “off” signal.
Immune checkpoint inhibitor drugs can be PD-1 inhibitors such as pembrolizumab (Keytruda), nivolumab (Opdivo), and cemiplimab (Libtayo), PD-L1 inhibitors such as atezolizumab (Tecentriq), avelumab (Bavencio), and Durvalumab (Imfinzi), and CTLA-4 inhibitors such as the aforementioned Yervoy.
More recently, CAR-T cells, another type of immunotherapy, have been used for the treatment of blood cancers like leukemia and lymphoma. CAR stands for chimeric antigen receptor.
CAR-T therapy involves extracting T cells from a patient’s blood sample. A special gene is put into the T cells in the lab, a gene called a chimeric antigen receptor (CAR). Millions of these CAR T cells are grown in the lab and then given to the patient by infusion. These CAR T cells can then bind to an antigen on the cancer cells and kill them.
In 2017, the FDA approved two CAR-T therapies — Kymriah for children with acute lymphoblastic leukemia and adults with large B-cell lymphoma, and Yescarta for adults who have relapsed or refractory diffuse large B-cell lymphoma.
These drugs are often costly, but there is hope that as they become more commonplace on the market, their price points will be more normalized.
Targeted therapy blocks receptors on cancer cell surfaces so that destruction can take place. Cancer cells have certain substances that make them different from normal cells. These substances are the targets for targeted therapies and they include:
- A certain kind of protein that exists in excess on a cancer cell
- A protein that doesn’t exist on a normal cell but does on a cancer one
- A protein that is in some way mutated compared to the same protein on a normal cell
- DNA (gene) changes that are not in a normal cell
Targeted therapies are primarily used in treating specific types of cancers such as bladder or prostate cancer. Examples of these drugs include:
- Angiogenesis inhibitors (bevacizumab, used for many different cancers)
- Monoclonal antibodies (alemtuzumab, for certain chronic leukemias, trastuzumab for certain breast cancers, cetuximab, for lung, head, neck, and colorectal cancers)
- Proteasome inhibitors (bortezomib, for multiple myeloma)
- Signal transduction inhibitors (imatinib, for certain chronic leukemias)
This type of therapy has been successful in shrinking the size of tumors, but it does not always work as well when cancer has spread to other parts of the body. Targeted therapies are often used with chemotherapy and radiation and may also be combined with surgery or hormone treatment.
Targeted treatments tend to have fewer side effects than systemic treatments and may be better at targeting cancer cells.
Aside from affecting cancer cells, traditional chemotherapy also causes a lot of damage to healthy cells in the body. In contrast, targeted drugs mostly harm only cancer cells and not healthy ones.
Additionally, targeted drugs can also prevent cancer cells from multiplying, meaning they stop a cancer cell from making new cancer cells. Traditional chemotherapy can only target cancer cells that have already been made.
Precision medicine refers to diagnosing and treating cancer based on an individual’s genetic makeup. This type of medicine in oncology looks at how a specific change in a gene might affect whether a person will get cancer or, if they already have cancer, it can help determine the best course of treatment.
For example, a person might notice that cancer runs in their family. They might meet with a genetic counselor who can tell them if they have genes that put them at risk for certain types of cancer. The testing can show if they have a gene change or mutation that puts them at risk. If so, the doctor might recommend screening and other tests (often at an earlier age) to help find cancer early. They might also prescribe medicines or suggest healthy habits to reduce the risk of getting cancer.
This branch of cancer research is still relatively new, and not all precision interventions are available yet on a broad scale.
Experts have debated the benefits and drawbacks. The most significant limitation to precision medicine is the fact that it can only be applied to cancers with specific gene mutations. Even cancers of the same type may not have the same gene mutation. A patient is a viable candidate for precision medicine only if they meet very specific criteria, which varies greatly depending on the type of disease.
That being said, many believe that precision medicine will be a game-changer with more extensive research.
Tissue biopsy is an essential step in identifying cancer. A biopsy can be done when there is a known or suspected tumor, but it can also be used to monitor the patient’s response to treatment or as part of routine screening.
Taking a tissue sample is not a pleasant experience and can be painful and debilitating for patients with weak immune systems.
An alternative to tissue biopsy is liquid biopsy – a procedure that is far less invasive given patients only need to provide blood or urine samples. Liquid biopsies are also more sensitive than traditional methods because they detect tiny traces of circulating tumor DNA (ctDNA), meaning that they can catch more cancers at an earlier stage.
This technology raises hopes that cancer diagnosis and monitoring will become easier to administer, more straightforward and far more accurate.
Machine learning (ML) is a branch of computer science that uses statistical techniques to allow computers to learn without being explicitly programmed.
Machine learning algorithms can predict future outcomes, identify patterns and anomalies in data, or classify items such as images. In cancer treatment development, machine learning has been applied for tumor detection from MRI scans, predicting different types of cancer, and importantly predicting cancer progression.
ML will continue to find new uses in medicine, such as predicting the severity of a disease, highlighting patterns in health data to identify potential side effects or new treatments.
ML also has multiple applications for precision medicine; doctors can use ML algorithms to predict which medical interventions will be most effective for different patients with cancer based on factors like age and tumor characteristics.
Other promising areas where machine learning can be applied include:
- Robotic surgery
- Robotic patient support tasks
- Personalized medicine
- Electronic health records (EHRs)
- Medical imaging diagnosis, and more
Challenges of New Cancer Treatment Development
Even though cancer research is an ongoing process, developing new successful treatments has not been easy, despite dedicated funding over the past five decades.
Some of the most common challenges that cancer treatment development faces today are related to the current structure of clinical trials, the nature of the disease itself, and poor access to essential data and resources.
Clinical trials are the most common way of discovering new cancer treatments. They typically consist of stages that gradually increase in patient sample size and complexity.
The main challenge with clinical trials is the time and cost associated with conducting a successful clinical outcome. Clinical trials can take up to a decade to complete and often cost hundreds of millions of dollars. This makes it difficult for researchers and the pharmaceutical industry to identify promising treatment candidates as quickly as possible.
Some companies are adapting their treatment research capabilities by creating specialized biotechs focused on specific types of cancers. Additionally, some institutions are turning to multi-arm, multi-stage clinical trials, such as the STAMPEDE trial in the UK.
The hope is that the current clinical trial model will be replaced by a more efficient and cost-effective one in the future.
A major hurdle in cancer treatment is the diversity of cells in a single tumor. This is called “tumor heterogeneity.” Different cells of the same tumor can react differently to a cancer drug. For some patients, it is near impossible to find one treatment or even a handful of treatments that can effectively diminish a tumor for good.
For example, high-dose chemotherapy only works on some cancers but doesn’t work on others; similarly, immunotherapy is effective against some cancers but not on others.
The range of mutations or “drivers” in cancer cells or in their tumor environment makes it difficult to find a set of treatments that will be effective on all types.
More importantly, in order for drug development and clinical trials to be successful, we need to identify treatments that work across various stages of cancer development – from the earliest forms that are hard to detect through late-stage cancers.
Access to Resources
Different institutions or organizations need to collaborate on the same project while developing an oncology treatment or product.
This requires access to the resources of each institution or organization.
For example, a pharmaceutical company trying to find new cancer treatments can request tumor samples from hospitals or universities with large databases of cancer patients and research data. They might also use computational power for their work at an institution’s high-performance computing center.
This kind of collaboration is not always seamless; many institutions have limited resources, and cancer researchers often feel pressured to choose one collaborator when they prefer to work with more than one.
Cancer research centers require better access to high-quality data, more computational power to run simulations and analyze large datasets quickly, and access to a larger number of samples for new treatment development to be as efficient as possible.
The global cancer research community is working on ways to overcome these challenges by defining common standards for data integration across institutions as well as standardizing the process of collecting tumor tissue before it’s too late.
One of the most significant obstacles for cancer research is the lack of high-quality data.
Genomic analyses can provide a wealth of information about what cancers look like in different tissues and how likely they are to respond to treatment. Yet, most datasets up to this point have been incredibly large and heterogenous, making it difficult to analyze them. Complex methods are required to extract information from such datasets, most notably a system that can manage their complexity and also adapt to specific characteristics of each analysis.
To address this issue, cancer researchers and the NIH-funded Cancer Genome Atlas (TCGA) have been working together for over ten years to create an open consortium of more than 25 research institutes to acquire genomic data from over 20,000 tissue samples.
TCGA has provided researchers with over 20 million data points of genomic information, which is a significant step forward in understanding how different cancers respond to treatment.
However, one problem that arises from having all this information available is deciding what research questions are worth answering based on previously-mentioned limited resources. Having an abundance of data still doesn’t mean much if it can’t be analyzed in a meaningful way.
Marketing Cancer Treatment
After the completion of clinical trials, the most crucial step is to find the drug’s target market and set a price for it, which can be challenging in some cases. Prescription drug price is not well regulated in the United States – pharmaceutical companies are free to increase their prices above inflation rates and irrelevant of the demand if they so choose.
Drug prices depend on:
- The uniqueness of the drug
- The effectiveness of the drug
- Competition from other pharmaceutical companies
- The R&D costs for bringing a drug to market
If the drugs are too costly, they will not impact cancer rates because lower-income patients cannot afford them. However, if they’re priced too low, there may not be enough money left for the pharmaceutical company to profit.
The FDA also needs to approve the drug before it can be marketed, which requires extensive review and testing that may take months or years for each submission. Drugmakers are constantly looking for ways of speeding up this process while still maintaining high standards in terms of treatment quality.
What is drug commercialization?
To put it in simple terms, cancer treatment commercialization is the process of transforming cancer treatment from drug research and development into a product that can be sold to the public.
It starts with pre-clinical trials, followed by three phases of clinical trials, at the end of which is the FDA approval. The most significant segments of drug commercialization are testing the drug safety, efficacy, and the FDA approval.
Once approval is acquired, the drug can be released to the public. This includes marketing the product, ensuring that patients are aware of it and that hospitals are stocked with necessary supplies.
The process also involves generating revenue for cancer treatment research at a company level.
- Securing funds
According to The National Center for Biotechnology Information, early stages (basic cancer research) are primarily funded by governments and philanthropic organizations. Pharmaceutical companies and venture capitalists support late stages and commercialization.
Before any marketing can take place, the company must secure the necessary funds. Many patented inventions do not make it through the product development pipeline because of their high cost. More resources are vital for cancer research to continue, which is one of the primary reasons that Music Beats Cancer was founded.
- Raising awareness among patients
A crucial factor in commercialization is informing the patients of the new treatment available on the market. A marketing department often handles this process. It includes utilizing traditional media, digital media, and reaching out through the patient’s physicians to inform them of the treatment.
Healthcare providers must ensure that their communication about the new treatment is accurate and transparent about any potential side effects.
- Building partnerships and alliances
Drugmakers need to establish partnerships and alliances with healthcare providers, payers, and patients for a successful treatment launch.
The company must also reach out to the physicians who will be using the treatment to provide them with information about it. They may need training on how best to administer a specific medication or device, for example.
Partnerships help generate buzz and create a sense of anticipation about the new treatment before it is launched.
Challenges of Commercialization
Commercialization of cancer treatment is a complex and challenging process.
Here is an overview of the biggest hurdles that need to be overcome:
- High Prices – Investors are reluctant to pay for the high prices of cancer drugs, and they are demanding more proof that new treatments are worth it. This is especially true for targeted therapies, which have a higher per-patient cost.
- Treatment Combinations – Healthcare providers are used to prescribing the same types of treatments for the same kinds of cancers. They are usually reluctant to deviate from the tried and true “standard of care” treatments. As a result, new treatment options will be under pressure to be combined with old drugs for physicians and patients alike to be more open to the idea of taking them.
- Massive Amount of Data – Finally, even though the ultimate goal is to make accurate decisions on the best treatment for patients, one of the most significant challenges doctors face is that there’s just too much data. Oncologists often have to sift through massive amounts of information about new treatments and try their best to decipher which treatments will be most beneficial for each patient.
While new types of treatments and solutions for cancer have been gaining momentum – i.e. immunotherapies, precision medicine, liquid biopsies – there are challenges that remain in the fight against cancer. These challenges related to both research and development and the process of commercializing new treatments.
To summarize, cancer treatment is developing at a rapid pace. There are many different ways to personalize therapy for each patient where improved results with minimal side effects can be achieved. The last decade has seen many so-called “breakthroughs” in cancer treatment. While these treatments have shown tremendous promise for those who have access to the latest medical technology, too often they are expensive – often prohibitively so – or not available at all if you live somewhere without state-of-the-art healthcare infrastructure.
Innovation is key to fighting disease, but along with new treatments and cancer-fighting solutions, affordability, education and access to medicine is vital for improved survival. Check out these innovative ideas for treating cancers.