Before a new drug or treatment can be tested in people, researchers usually study it in the lab first. This stage is called preclinical research.

These studies help scientists learn how a treatment works, how safe it may be, and whether it should move forward. Preclinical research can include cell studies, animal models, computer tools, and other testing methods.

The results do not prove that a treatment will work in people. However, they can give researchers important information before clinical trials begin.

Define the main goal of preclinical research

The main goal of preclinical research is to study a new treatment before it reaches human testing. Researchers want to understand both its possible benefits and its risks.

One key question is whether the treatment has the effect scientists expect. For example, a new cancer drug may be tested to see whether it slows the growth of certain tumour cells.

Safety is just as important. Researchers also look for signs that the treatment may harm healthy cells, organs, or body systems.

This early work helps teams decide whether the treatment needs more study, should be changed, or is ready for the next stage.

Start with basic laboratory research

Many preclinical projects begin with basic laboratory work. Scientists may first study a disease, a cell type, or a biological process.

This stage helps researchers understand what may be causing the disease. It can also help them identify possible targets for new drugs or treatments.

Once a target is found, researchers may test different compounds to see which ones have the strongest effect. Most early ideas do not move very far.

The strongest candidates are then studied in more detail. This process helps research teams focus their time and money on the most promising options.

Use in vitro testing

In vitro testing means studying a treatment outside a living body. Researchers often use cells, tissues, or other biological material in a lab setting.

These studies can help show how a drug interacts with certain cells. Scientists may test whether the treatment changes cell growth, survival, or another process.

In vitro testing is useful because researchers can control the conditions closely. They can change one factor at a time and watch what happens.

However, cells in a dish cannot copy the full complexity of a living body. For this reason, in vitro studies are usually only one part of a larger preclinical program.

Explore different cell models

Not all cell models are the same. Researchers may choose different types depending on the disease or treatment being studied.

Some models use standard cell lines that have been used in research for many years. Others may use cells taken from patients or grown in more complex ways.

Researchers can compare several models to see whether a treatment works in more than one setting. This can provide a broader view of its possible effects.

Using the right model matters because weak or poorly matched models may give results that are less useful later.

Move into in vivo studies

In vivo studies take place in a living organism. These studies help researchers see how a treatment behaves in a full biological system.

A living body can show effects that cannot be seen in a simple cell model. For example, a drug may work well on cells but break down too quickly after it enters the body.

Researchers may also study how the treatment affects several organs at the same time. This can reveal possible safety concerns.

In vivo studies can therefore give a more complete picture of both treatment effect and risk before human testing begins.

Study how the drug moves through the body

Researchers often study pharmacokinetics during preclinical work. This term describes what the body does to a drug.

It includes how the drug is absorbed, where it travels, how it is changed, and how it leaves the body. Each of these steps can affect how well the treatment works.

Scientists may collect blood or tissue samples at different times. They can then measure how much of the drug is present.

This information helps researchers understand how long the treatment stays active. It can also support early planning for dose levels and how often a treatment may need to be given.

Use disease models to study treatment response

Preclinical studies often use models that copy certain parts of a human disease. These models can help researchers see whether a treatment works in a more realistic setting.

In cancer research, for example, tumour models may be used to study how a new drug affects tumour growth. Different models may represent different cancer types.

Research teams may also use specialised platforms such as XenoSTART when studying how cancer treatments perform in preclinical oncology models.

No model can fully copy a human disease. Still, well-chosen models can give researchers useful evidence about whether a treatment should continue to the next stage.

Study what the drug does to the body

Pharmacodynamics looks at what the drug does to the body. It focuses on the treatment effect and how that effect changes at different dose levels.

Researchers may study whether the drug reaches the intended target. They may also measure changes in cells, tumours, or other signs linked to the disease.

This work can help show whether a stronger dose leads to a stronger effect. It may also reveal a point where adding more drug no longer helps.

Pharmacokinetic and pharmacodynamic studies are often reviewed together. This gives researchers a clearer view of how dose, exposure, and treatment effect are connected.

Test for possible toxic effects

Safety testing is one of the most important parts of preclinical research. Researchers need to know what harmful effects may appear before a treatment is tested in people.

Toxicity studies may look at the liver, kidneys, heart, blood, nervous system, and other organs. Researchers may also monitor behaviour, weight, and other health changes.

Some tests study the effect of one dose. Others look at repeated doses over a longer period.

The goal is to find out where problems may begin. This information can help guide later decisions about dose levels and safety monitoring.

Compare different dose levels

Dose testing helps researchers learn how much of a treatment may be needed to create an effect. It also shows when side effects may begin to appear.

Several dose levels are often tested in the same study. Researchers can compare treatment response and safety at each level.

This may help them find a range where the treatment appears active without causing too much harm. That range can be useful when planning later studies.

The starting dose for human trials is chosen very carefully. Preclinical dose data can help support that choice, but other safety factors are also considered.

Study tumour and oncology models

Cancer research often requires special preclinical methods. Tumours can behave differently depending on their type, location, and biological features.

Researchers may use models that allow them to study tumour growth over time. They can compare treated groups with untreated or standard-treatment groups.

This can show whether a new drug slows tumour growth, causes shrinkage, or has little effect. Researchers may also look for changes in certain biological markers.

These studies can help teams understand which types of tumours may respond best. This can later guide decisions about which patients may be included in early clinical trials.

Measure clear study outcomes

Every preclinical study needs clear outcomes. These are the results researchers plan to measure.

The outcome should match the main goal of the study. In one project, researchers may measure tumour size. In another, they may study cell survival, organ function, or drug levels.

Clear outcomes make results easier to compare. They also reduce confusion about what the study is trying to prove.

Researchers should decide on these outcomes before the study begins. This helps keep the work focused and makes the final data easier to review.

Use control groups for better comparisons

Control groups are an important part of many preclinical studies. They give researchers a clear point of comparison.

A control group may receive no treatment, a placebo, or a standard treatment. The exact choice depends on the purpose of the study.

Researchers can then compare the control group with the group receiving the new treatment. This helps show whether changes are likely linked to the treatment itself.

Without a useful control group, it may be harder to understand the results. Good comparisons make the study stronger and easier to interpret.

Reduce bias in study design

Bias can affect research results if a study is not planned carefully. Researchers use several methods to reduce this risk.

Randomization is one common method. It means assigning subjects to groups in a way that avoids unfair selection.

Blinding may also be used. In some studies, the person checking the results does not know which subjects received the new treatment.

These steps do not remove every possible source of error. However, they can make the results more reliable and reduce the chance of personal expectations affecting the findings.

Record and manage data carefully

Good data records are important throughout preclinical research. Researchers need to track exactly what happened during each study.

Records may include dose levels, treatment times, test methods, observations, lab results, and outcomes. Clear records make it easier to review the work later.

Many research teams use digital systems to store and organise information. This can help reduce mistakes and make large sets of data easier to manage.

Good records are also important when results are shared with other researchers, companies, or regulators. Missing information can raise questions about the quality of the study.

Learn from negative results

Not every preclinical study produces a positive result. Some treatments may show weak effects or create safety concerns.

These results are still valuable. They can show that a drug needs to be changed, tested at a different dose, or stopped.

Finding a problem early can save time and money. It can also prevent a weak or unsafe treatment from moving into human trials.

Negative results can also help researchers improve future projects. Understanding why something did not work can lead to better study design or new treatment ideas.

Prepare data for regulatory review

Before a new treatment can enter human testing, research teams may need to submit preclinical data to health regulators.

Regulators review the evidence to decide whether a planned clinical trial appears safe enough to begin. They may look at toxicology, dose studies, drug behavior, and study methods.

The information must be clear and complete. Research teams may need to explain how studies were done and why certain models were used.

Regulators may ask for more information if important questions remain. 

Connect preclinical findings to clinical trials

Preclinical research helps shape the first stages of human testing. The results may guide starting doses, safety checks, and study goals.

Researchers may also use the data to decide which patients may be most suitable for early trials. This can make the clinical study more focused.

Some preclinical results may also suggest which signs or biomarkers should be measured in people. These markers can help show whether the treatment is having the expected effect.

Still, human biology is more complex than any lab model. That is why clinical trials are needed even after strong preclinical results.

Understand the limits of preclinical research

Preclinical studies provide useful information, but they have limits. A treatment that works well in a model may not work the same way in people.

Differences in biology can change how a drug is absorbed, how it reaches its target, and how the body responds.

Animal and cell models also cannot fully copy the full range of human disease. Age, genetics, other health problems, and many other factors can affect treatment response in people.

Researchers must therefore avoid treating preclinical success as proof of clinical success. 

Preclinical research builds the bridge to human testing

Preclinical trials are a key step in the development of new drugs and treatments. They help researchers study safety, dose, drug behaviour, and possible treatment effects before human testing begins.

Strong study design, clear outcomes, careful data handling, and useful disease models all improve the quality of the research. Negative results are also important because they can prevent weak ideas from moving forward.

Preclinical success does not guarantee success in people. Still, these studies help reduce risk and give research teams a stronger base for clinical trials.

By combining careful testing with clear evidence, preclinical research helps move promising treatments from the laboratory toward possible use in human medicine.

Amelia Hart, a psychology graduate from the University of Hertfordshire, has a keen interest in the fields of mental health, wellness, and lifestyle.