Clinical trials and data for laypeople, Part 3

Initial investigation of a therapy in humans starts with a phase I clinical trial. Phase I is extremely preliminary. Its purpose is really just to verify whether the therapy can be used in humans at all. It identifies the safe range for therapy dosage and any side effects patients may experience. In phase I, a therapy is given to a very small number of people, tens of people as opposed to thousands like clinical trials in later phases.

In phase I studies, you often see many diagnoses being tested at once. For example, it is not unusual for phase I cancer trials to look at solid tumors. There could be dozens of reasons for a patient to have a cancerous solid tumor. Phase I studies are small. But when they look at several different diseases, you get an even smaller number of patients. For example, let’s say a phase I cancer trial is looking at testing New Drug X in patients with solid tumors. A total of twenty patients will participate in this study. Of those twenty patients, five may have non-small cell lung cancer and two may have colorectal cancer. So you are looking at tiny numbers of people. You are trying to prove that this therapy can be used in humans at all rather than looking at how well it works on a particular disease.

Phase II is when you start to get into the real meat of trialing a therapy. In this phase, a few hundred people are recruited. At this point, the targeted diseases are clearly defined. You don’t see tons of diagnoses being trialed like you might see in Phase I. The goals of a phase II trial are to figure out which dose is the best for treating a disease and to identify any side effects or toxicities a patient may experience from taking the therapy.

In phase II trials, trial design is less uniform. This means that not all phase II trials follow the same pattern. They are sometimes divided into two parts, called phase IIa and phase IIb. Phase IIa trials are usually dedicated to figuring out what dosage should be given to patients. In phase IIb, the studies investigate what dosage gives the best result for patients and cause the lowest level of toxicity and complications, called adverse events.

Most people are familiar with the clinical trial format where some patients get the therapy and some patients get a placebo, and neither the patients nor the investigators know who gets what until the end. This doesn’t always happen, especially in oncology and rare disease trials. For very aggressive diseases, the reason is that getting the placebo and therefore not receiving any treatment would be fatal. In such instances, some patients might get the new therapy while others would get an older therapy that is currently used for people with that disease. When a treatment plan is typically prescribed for patients with a particular diagnosis, that treatment is called the standard of care (SoC). When you read through trial data or articles about trials, you might see something like “[drug name] vs SoC”. This means that some patients get the new therapy and some get the old therapy. The patients may or may not know which therapy they are getting. This depends a lot on the disease and how the new therapy and the standard of care are administered. For example, a new therapy might be given intravenously twice a month. The standard of care could be radiation therapy once a month. For obvious reasons, patients and investigators will know what therapy they are getting. But if both treatments are given via IV twice a month, the patients may not know. The investigators may or may not know depending on the trial design.

In certain situations, a phase II trial might be designed not to compare a new therapy to standard of care, but instead to demonstrate that a therapy can be given safely at a particular dose and have the intended effect upon a disease. This might happen if there is no standard therapy available for a disease. It also happens in rare disease studies because they want to get as much data on how a therapy affects patients with the rare disease and, by nature, there aren’t a lot of patients with that rare disease. So in a study for Rare Disease Y, instead of giving 100 patients the new therapy and 100 patients the standard of care, the investigators may choose to give all 200 patients the new therapy so that they can get as much data as possible on how this drug affects patients with this rare disease.

After phase II studies, the data collected and analyzed is submitted to the regulatory body for countries where the investigators want to be able to use the drug. In the US, this is the FDA. The data is reviewed and the regulatory body will decide what the next step is to be able to use the therapy in people.

There are several possible paths from this point. The regulatory agency may decide that the data is not strong enough to show that the drug works at a particular dose safely in patients while helping their disease. They could tell the investigators to extend their phase II trial, or to design a new trial and try again. They could tell the investigators that they feel the therapy is dangerous and not eligible for use in humans. They could agree the data supports the use of the therapy in this patient population, but want to see more data on a larger population. In this instance, the next step is a phase III trial.

In scenarios where the therapy is demonstrably effective against a disease and relatively safe to use in humans, the regulatory body could also elect to approve the therapy for use immediately. In this case, no phase III trial would be needed to approve the therapy for a particular disease indication. This happens mostly in situations where there is no effective therapy currently for a disease. This has happened in rare disease trials.

Clinical trials and data for laypeople, Part 2

The foundation of science is this: that we can determine how adding or removing something changes a scenario by comparing it to what happens when we do not nothing.

Sunblock is a very simple example of this. In order to see what sunblock does, or does not do, we first keep track of what happens when a person doesn’t use sunblock, and then replicate that situation with the only change being that person now using sunblock. It is important to keep everything else the same: if the person we are testing normally drinks three cups of coffee before noon, wears make up, and doesn’t get enough sleep, we want that person to keep doing those things while we study what the sunblock does.

The reason we want this is because if lots of things change at once, how can we know that the sunblock causes any changes we see? For example, let’s say this person often has an upset stomach. If she suddenly stops drinking coffee when she starts using sunblock, and this improves her upset stomach, the data might indicate that wearing sunblock helps with upset stomach even though that’s not really the case.

Most people think that clinical trials do what I just described: that they compare the effect of a therapy to people who think they are getting the therapy but are actually getting the placebo. While this does sometimes happen, that is almost never the case for people with advanced life threatening diseases or rare diseases. This is a complex topic so I’m going to unpack this in a series of posts so that I can answer questions as they come up.

The first thing to understand is that there are phases of clinical trials. Understanding the phases will help you to know what the data means when the results are released.

For trials that are supervised by the American FDA, there are four phases. They are cleverly called Phase I, Phase II, Phase III, and Phase IV.

Phase I is the first and most preliminary. Phase I trials are safety and dosing trials. I have never seen a phase I trial with more than fifty people. Most of the ones I see involve 10-20 people. This is the first real contact a new treatment (drug or biologic) has with patients that the therapy is intended to treat. It is literally to see how the human body reacts when it is given any amount of this substance.

Phase I trials are to see what adverse events present with this therapy. Adverse events are basically side effects and complications. They are the risks you accept when using the therapy. Some are serious, and some are not.

Dosing trials are just what they sound like: they give different people different doses in order to figure out the lowest effective dose. This is because we want to give as little of this substance as possible because this usually gives the lowest risk for complications. So we will split our phase I group into smaller groups called cohorts. Cohort is just the science term for a group of patients that have things in common that we are studying.

For example, let’s say we have a phase I study for Klimasonium, a drug that is taken once daily and cures mast cell disease. (I super wish for Klimasonium.) Let’s say I gather up 30 patients with MCAS for Klimasonium. (Please do not think this is real thing.) In order to determine what doses we should use to treat patients, I would break up my 30 patients into 3 groups, also called cohorts. Cohort 1 would take one tablet a day. Cohort 2 would take two tablets a day. Cohort 3 would take three tablets a day.

At the end of the trial, I would look at what side effects and complications patients had, and if their disease got worse or better, and in what ways. Based upon this information, I will pick a dose that helps the disease while causing the fewest complications. I will also have to report any and all side effects or complications to the FDA so that the risks of this therapy are recorded and patients who take this drug at any time will be made aware.

Clinical trials and data for laypeople, Part 1

Hey, MastAttackers,

We are going to take a short break from the 107 series to address a topic I get asked about constantly: which drugs are best for advanced systemic mastocytosis and how they compare to one another.

Before we get started, there are some things we need to get out of the way. While my second life revolves around educating about mast cell disease and helping patients (and my third life involves having mast cell disease and living with it), my first life and real world job is as a senior scientist for the biomedical research division of a large pharma organization. My job is to figure out ways to test for things that will tell us if a patient is likely to get benefit from the therapies we are testing in studies and clinical trials to treat diseases. While my job largely focuses on supporting trials for cancers like lung cancer and melanoma, I also contribute to trials for rare diseases. One of the rare diseases we have trials for is systemic mastocytosis.

Nothing I say here or in my capacity as Lisa Klimas from MastAttack or Lisa Klimas, a human with systemic mastocytosis, should be taken as representing the organization I work for. I do not ever speak as an employee about the things I just mentioned unless I am at work working. Ever.

Obviously, I have systemic mastocytosis. Everyone knows that. This is not a secret. Systemic mastocytosis is the center of the Venn Diagram of my three lives: they all touch there. For this reason, I avoid talking about certain things about my health because it triggers questions about things that relate closely to my job. For the same reason, I am also very restricted in what I can say about certain therapies for systemic mastocytosis. Specifically, I am very restricted in what I can say about therapies for advanced systemic mastocytosis, like tyrosine kinase inhibitors and multitarget kinase inhibitors.

However, I can talk about how to compare two therapies to one another using science, and you can apply that however you wish. So for the next several posts, I’m going to give a crash course in drug development, clinical trials and data interpretation for laypeople. If you have specific questions, please comment on this post. I will answer any question in a post provided it does not violate my obligations I mentioned above. First post goes up tomorrow night and covers how clinical trials work, what the phases mean, and how people with no science background can understand what the results mean.

Hope this helps clear things up. This will be fun.