Developing a drug costs an estimated US$2.6 billion. Since 9 out of 10 drug candidates never reach the market, much of this money is wasted as decades of potential new drug targets have yet to be exploited. The study of drugs that affect living systems allows us to understand why these changes occur, allowing us to develop better drug therapies.
But how far has drug discovery really evolved and what factors should be taken into account in developing new ones?
A Brief History
Over the past 50 years, new drugs and therapeutic agents have transformed modern medicine. Diseases that are now rare, preventable and/or treatable, such as pneumonia, tuberculosis, and diarrhea, were responsible for countless deaths in the 20th century. And while they still affect thousands of people worldwide, more complex conditions, such as cardiovascular disease and cancer, can be targeted and, to some extent, treated thanks to medical breakthroughs. With improved sanitation and immunization and the increasing availability of drugs to control and cure disease, our collective health and life expectancy have only improved.
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Synthetic chemistry gave rise to the idea that any conceivable drug could be manufactured and synthesized. As synthesis became more sophisticated and affordable, the ability to fine-tune or optimize the activity of known drugs improved. The increasing commercial availability of powerful spectrometry techniques, such as nuclear magnetic resonance and mass spectrometry, and separation techniques, such as high-performance liquid chromatography, made it possible to establish structural information about biologically active natural products, while advances in X-ray crystallography revealed the three-dimensional protein structures for rational drug design studies.
With the increase in computing power and progress in structural biology during the 1980s, a more rational approach to drug discovery was adopted. Instead of randomly searching for active natural products, rational design involves predicting how the structure of a molecule will affect its behavior to create new molecules with specific functionality. The sophistication of high-throughput screening and progress in biological techniques have also played an important role in recent drug development by screening thousands of compounds simultaneously and improving target characterization and validation, so that drugs are more likely to succeed in clinical trials.
And although in silico modelling and design techniques have been important in drug research and development (R&D), we witnessed a decline in pharmaceutical R&D productivity, known as Eroom’s Law (Moore’s Law spelled backwards). Eroom’s Law is the observation that the number of new drugs approved per billion US dollars spent on R&D is a decreasing trend.
According to Thomas Chittenden in a 2018 Nature article, “AI is going to lead to the full understanding of human biology and give us the means to fully address human disease.” Today, advanced artificial intelligence and machine learning (AI/ML) algorithms are being used for drug discovery, often to recognize patterns in large volumes of biological data or analyze relationships between biological entities. Whether the application of AI/ML to drug discovery can truly address the downward trend of Eroom’s Law with faster, cheaper, and better drugs is a matter we will find out in a few years.
Pharmacokinetics and Pharmacodynamics
Pharmacology is the study of interactions between a living organism and drugs or medications that influence biochemical function. It is concerned with the research, discovery, and characterization of chemicals with biological influences and the understanding of cellular function in relation to these chemicals. Not to be confused with pharmacy, which is the study of health sciences aimed at applying pharmacological principles to the clinic, pharmacology is more science-based. The two main areas of pharmacology are pharmacodynamics and pharmacokinetics.
Pharmacokinetics (PK) is concerned with how the body handles the drug. The drug’s journey through the body involves 4 processes : absorption, distribution, metabolism, and elimination/excretion, abbreviated to ADME. Assessing ADME is critical in pharmacokinetics studies, letting researchers know if a drug is viable and providing certain targets for future R&D.
When the drug enters the body through a route of administration, such as ingestion or injection, it goes through the absorption stage. The extent to which absorption occurs or the fraction of the drug that reaches the systemic circulation is known as bioavailability. If a drug is administered intravenously, its bioavailability is 100%; oral bioavailability tends to be lower because the drug may not be completely absorbed or metabolized.
The next phase, distribution, depends on tissue permeability, blood flow, molecular size, and binding to plasma proteins or additional cellular components. Once absorbed, the drug moves to different parts of the body via the bloodstream or from cell-to-cell. When drugs bind to proteins in the body, their passage across biological membranes and barriers is limited. Because drug-protein complexes often have a high molecular weight, there is an accumulation of the drugs and a considerable reduction of their desired activity.
When a drug is transformed by organs or tissues in the liver, kidney, skin, or digestive tract, it undergoes metabolism. At this stage, toxic metabolites or damaging byproducts can be created, so analyzing the body’s metabolic response to a drug is critical. At this point, the drug becomes more water-soluble to facilitate excretion.
At the final stage of elimination or excretion, compounds and their metabolites need to be removed from the body. Metabolic waste is mainly excreted as feces or urine, but it may also leave the body through the lungs or the skin. If a drug compound isn’t fully excreted, the chemical or metabolic byproducts bioaccumulate and adverse effects can occur.
Pharmacodynamics (PD), on the other hand, is concerned with how the drug affects the body. Drug action (the initial consequence of a drug-receptor interaction or the chemical action or physicochemical properties of a drug) and drug effect (the resulting effects) characterize the drug response. The PD of a drug may be affected by physiological changes due to disease, genetic mutations, aging, or other drugs, because these conditions can change receptor binding or post-receptor response, alter chemical interactions and binding protein levels, or decrease receptor sensitivity.
Unlike PK (which quantitatively studies ADME), PD (which studies the biochemical and physiological effects of drugs) is difficult to quantify. Both PK and PD explain the drug’s effects, which is the relationship between the dose and response.
Forward vs. Reverse Pharmacology
Traditionally, compounds are screened in cellular or animal disease models to identify those that cause a desirable change in phenotype. The compounds that demonstrate a desirable therapeutic effect are analyzed and inspected for their biological targets, such as proteins (usually enzymes, ion channels, and receptors) and nucleic acids. This is known as classical pharmacology, forward pharmacology, or phenotypic drug discovery.
More recently, the popular and modern approach to drug discovery is reverse pharmacology or target-based drug discovery, which begins by identifying a certain disease-related biological target and then searching for a molecule known to bind to it with high affinity. Once lead compounds are found, they can be tested on living cells to assess their therapeutic and adverse effects. By starting with a problem and working backwards, reverse pharmacology is considered to be the most effective — and often the fastest — way to discover a new drug.
Genome analysis is the foundation of this approach, as the human genome has enabled the rapid cloning and synthesis of large quantities of purified proteins. This method is now the most widely used in drug discovery.
Gaining a deeper understanding of the past and present of pharmacology raises the question on the future of drug discovery and development.
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