Drug Discovery Demystified: How We Find Cures for Diseases
How do you start a drug discovery program? I've been asked this question countless times by family, friends, and experts from other fields, prompting me to write this article. While not intended as a comprehensive scientific review of drug discovery, this piece aims to provide an informative overview. Whether you're a curious student, a concerned patient, or simply someone who's ever wondered how that pill in your medicine cabinet came to be, this guide will walk you through the fascinating world of drug discovery – no PhD required.
Today, we'll explore the process of finding a cure for a disease from first principles. Let's work through developing a drug to treat a form of cancer, using this example to outline general principles of drug discovery that can be applied to other diseases. Before delving into cancer treatments, I'll provide a brief overview of fundamental biology concepts. This background will prove invaluable as we tackle complex biological problems in our quest for cancer therapies.
DNA, RNA and Proteins: The Central Dogma of Biology
Imagine your body as a vast metropolis built from tiny building blocks called cells. While most cells are microscopic, some, like the ovum (egg cell), are actually visible to the naked eye. Each cell, though incredibly complex, can be simplified into three main components: an outer cell membrane, a bustling cytoplasm (containing various structures like mitochondria), and a control center called the nucleus. Inside this nucleus lies DNA, the blueprint of life (though it's worth noting that DNA is also found in mitochondria, but we'll set that aside for now). DNA consists of two long chains, each composed of a sequence of four "letters": A, T, G, and C. These letters have a special property – they form complementary pairs (A with T, G with C) across the two strands. This pairing causes the strands to coil around each other, forming the famous "double helix" structure. But there's more! This double-stranded DNA doesn't float freely. It's wrapped around proteins called histones, and this DNA-histone combo forms what we call a chromosome. In healthy human cells, you'll find 23 pairs of these chromosomes.
Now, you might be wondering, "What about genes?" A gene is essentially a segment of a chromosome that contains information to make a specific protein. Think of DNA as a computer's hard drive, storing information about what proteins to make and when (though the timing aspect, controlled largely by epigenetics, is a complex topic for another day).
Proteins are the true workhorses of our cells, performing various tasks to maintain cellular order. But we can't forget about RNA! RNA primarily acts as a messenger, ferrying information from the DNA in the nucleus to the protein-building factories (ribosomes) in the cytoplasm.
When everything's running smoothly, DNA, RNA, and proteins work in harmony to keep every cell in your body healthy. However, in disease states, one or more of these biomolecules misbehave. Your DNA might mutate, your RNA could be modified or broken down differently, or your proteins might undergo unexpected changes. Mutations come in many forms, but let's focus on the simplest type: the substitution point mutation. This occurs when one letter in the DNA sequence is swapped for another – for example, an A changing to a T. Such a change could lead to downstream effects, potentially modifying proteins either directly due to the DNA mutation or indirectly through the actions of other proteins.
While this is undoubtedly a simplified view of an incredibly complex system, the key takeaway is this: in disease states, one or more of these crucial biomolecules exists in an abnormal state, disrupting the cellular harmony.
From Biology Basics to Battling Breast Cancer
Now that we've taken our whirlwind tour of basic biology, let's apply this knowledge to tackle a real-world problem: finding abnormalities in breast cancer.
Historically, cancers were classified by their location - breast cancer in the breast, lung cancer in the lungs, and so on. But science marches on! Thanks to advancements in genome sequencing technologies, we now know that cancers in a single organ can actually be classified into different genetic diseases. Remember how we discussed that cancer can result from abnormalities in various biomolecules? This is where that knowledge comes into play. You might be thinking, "Wait a minute! If we have these fancy genome sequencing technologies, shouldn't it be easy to find the abnormal mutation in the DNA and target it with a drug?" If only it were that simple! Cancer, unfortunately, is a far more complex beast. It's rare for a single mutation to cause cancer. Instead, it's usually the result of many different types of mutations working in concert.
These mutations come in various flavours: substitutions, deletions, insertions, translocations, copy number variations, and more. Don't worry if these terms sound like alphabet soup - the key takeaway is that DNA can change in many places and in several ways within a cancer cell. But fear not! There's a silver lining to this mutational cloud. While cancer cells may harbour numerous mutations, there are usually key "driver" mutations that play a starring role in the growth and progression of the cancer. If we can identify these driver mutations/key abnormalities, we have a potential target for our cancer-fighting efforts.
This process of pinpointing the correct abnormalities in biomolecules responsible for causing a disease is known as "target identification" in the drug discovery world. It's a crucial step because if we can develop a drug that mitigates the abnormalities in the target biomolecule, we have a shot at treating the disease. So, while the path from understanding basic biology to developing cancer treatments is complex, it's not insurmountable. By focusing on these cancer drivers, scientists are continually advancing our ability to combat cancer at its genetic roots.
From Biopsy to Breakthrough: The Challenge of Cancer Research
Let's dive back into our breast cancer scenario. Picture this: a dedicated clinician in a cancer hospital performs a biopsy on a breast cancer patient, carefully extracting a tiny sample of cancerous tissue. This precious sample is then whisked away to eager researchers armed with cutting-edge technology.
What happens next is nothing short of scientific wizardry. The researchers unleash a barrage of tests on this tiny tissue sample: genome sequencing, proteomics, epigenetics sequencing - collectively known as "omics" technology. It's like putting the cancer under a high-powered microscope that can see down to the molecular level, allowing us to spot those abnormalities we discussed earlier. The data analysis from these experiments is truly staggering - hence all the buzz about "big data" in drug discovery. After sifting through this mountain of information, researchers typically end up with a list of 10-100 biomolecule abnormalities they suspect are driving the cancer's growth and progression.
But here's the rub: in this process of discovery, researchers have used up almost all of that precious biopsy tissue. They've extracted every bit of DNA, protein, and RNA they could from those cancerous cells. It's a bit like burning through all your fuel just to map out your journey, leaving little for the actual trip. This leaves them with a tantalizing list of potential targets, but hardly any original cancer tissue left to verify if these targets are truly meaningful.
This is where cancer model systems come to the rescue. You see, cancer cells have an insatiable appetite for growth - a curse for patients, but a boon for researchers. Given the right nutrients, these cells can grow continuously in plastic plates in the lab, becoming essentially immortal. They can be stored in liquid nitrogen, like tiny time capsules of disease, ready to be thawed and used for experiments as needed. These cancer cell lines provide researchers with an renewable resource for their studies. Instead of exhausting precious patient samples, they can use these immortalized cells to dive deeper into their list of potential targets, verifying which ones truly hold the key to fighting the cancer.
The Rocky Road of Drug Discovery: Challenges and Complexities
We're about to dive into the challenging world of drug discovery, where the stakes are high, and the path is far from smooth.
First, let's talk numbers. Brace yourselves: bringing a single drug to market costs around $1 billion. Yes, you read that right - billion with a 'B'. And here's the kicker - only about 10% of drugs entering Phase 1 clinical trials actually make it to approval. For those of you craving more details on these eye-watering figures, check out this article in JAMA (2020, 323(9) 844-853).
So, why such a high failure rate? One major culprit is the difficulty in identifying the correct target for a disease. Even after years of careful experimentation, pinpointing the right biomolecule to target is like finding a needle in a molecular haystack. Let's break down some of the key challenges:
The Model Dilemma: Remember those immortal cancer cell lines we talked about? These cancer cell lines are vital in drug discovery pipelines because it is not practical to use biopsies from cancer patients in every experiment. While the cancer cell line models are incredibly useful, they're not perfect. Real tumours are a diverse bunch, with a variety of cell types and mutations, surrounded by a complex microenvironment (think blood vessels, inflammatory cells, and more). Our lab-grown cancer cells lack this complexity. They can even change genetically over time, drifting away from the characteristics of the original cancer.
There are alternatives, like Patient Derived Xenografts (PDXs) - human tumors grown in mice. These capture more of the tumor's complexity but come with their own debates and practical challenges. PDXs are not as easy to use as the cancer cells that grow in plastic plates. Although, PDXs sound great and clearly superior to cancer cells, they are grown on mice and are not very easy to produce and use. Therefore, there is a lot of research going on in this space of developing cancer models which are better than cancer cells that can be grown in labs such as organoids and 3D cultures.
Lost in Translation: Just because something works in a petri dish doesn't mean it'll work in a patient. A lot of target validation involves techniques like CRISPR to knockout genes or RNA interference to reduce protein levels. If knocking out protein X makes cancer grow faster, we might think targeting it could slow cancer down. Although such experiments sometimes provide meaningful results and list of proteins to target, there are several important caveats to these experiments. Cancers are complex diseases and do not just involve a handful of proteins, therefore it is not always possible to study the subtle interplay of many proteins in cancer using these experiments. Another caveat is that the pharmacological intervention using a synthetic molecule by binding to the target does not always produce the same effect as completely removing or reducing the amount of the target protein.
Resistance: Another crucial challenge in cancer drug discovery is the remarkable adaptability of cancer cells. Cancer cells evolve to escape the action of drugs over time, building resistance. This ability to adapt and survive is one of cancer's most formidable traits. As we develop new treatments, cancer cells often find new ways to circumvent them, leading to drug resistance. This ongoing battle between our treatments and cancer's evolution adds another layer of complexity to drug discovery, pushing researchers to constantly innovate and stay one step ahead of these crafty cells.
This is just a glimpse into the complex world of target identification in drug discovery. It's a field so vast and intricate that we've barely scratched the surface here. But fear not! We'll be diving deeper in future articles, exploring specific examples of how researchers navigate these challenges to bring new treatments to those who need them most.
To stay updated on future articles where we'll explore more examples, tackle new challenges, and unravel more secrets of drug discovery, don't forget to hit that subscribe button. By subscribing, you'll be first in line for our upcoming deep dives into specific target identification case studies, explorations of cutting-edge research techniques, and more insights into the ever-evolving landscape.