It’s important to lay strong foundations for successful drug discovery at this first stage of the process. Our integrated target identification and validation platform combines AI with expert insights, and rigorous lab validation to guide targets through robust evaluation, ready for hit discovery.
Validated, high-quality hits, delivered through integrated technologies and expert collaboration, give you a confident starting point for faster drug discovery.
Turning promising leads into clinical candidates with speed, precision, and the scientific expertise to generate high-quality data and deliver real patient impact.
Delivering integrated, modality-agnostic drug discovery to tackle complex biology, accelerate development, and advance innovative therapies with confidence.
Advancing next-generation ADCs through payload-focused design, integrated expertise, and collaborative innovation to deliver safer, more selective therapies.
Driving biologics innovation through integrated design, structural biology, and multidisciplinary expertise to accelerate next-generation therapies from concept to clinic.
Combining deep therapeutic expertise with translational insight to design strategies, reduce risk, and accelerate discovery programs toward clinical success.
Accelerating oncology drug discovery through integrated expertise, innovative modalities, and translational insight to deliver candidates with real clinical impact.
Driving immunology and inflammation drug discovery through tailored assays, translational models, and integrated expertise for faster clinical success.
Advancing CNS drug discovery through integrated models, translational biomarkers, and multidisciplinary expertise to overcome complexity and accelerate therapeutic innovation.
Designing and advancing differentiated small-molecule therapies for obesity and diabetes through integrated expertise, mechanistic insight, and translational strategies.
Inobrodib, an exciting, first-in-class oral anti-cancer drug in clinical development by CellCentric, was collaboratively designed, synthesised and supported on its pre-clinical journey by an integrated project team at Sygnature Discovery. Inobrodib is now showing promising results in Phase I and II trials for multiple myeloma and other cancer types.
It’s important to lay strong foundations for successful drug discovery at this first stage of the process. Our integrated target identification and validation platform combines AI with expert insights, and rigorous lab validation to guide targets through robust evaluation, ready for hit discovery.
Validated, high-quality hits, delivered through integrated technologies and expert collaboration, give you a confident starting point for faster drug discovery.
Turning promising leads into clinical candidates with speed, precision, and the scientific expertise to generate high-quality data and deliver real patient impact.
Delivering integrated, modality-agnostic drug discovery to tackle complex biology, accelerate development, and advance innovative therapies with confidence.
Advancing next-generation ADCs through payload-focused design, integrated expertise, and collaborative innovation to deliver safer, more selective therapies.
Driving biologics innovation through integrated design, structural biology, and multidisciplinary expertise to accelerate next-generation therapies from concept to clinic.
Combining deep therapeutic expertise with translational insight to design strategies, reduce risk, and accelerate discovery programs toward clinical success.
Accelerating oncology drug discovery through integrated expertise, innovative modalities, and translational insight to deliver candidates with real clinical impact.
Driving immunology and inflammation drug discovery through tailored assays, translational models, and integrated expertise for faster clinical success.
Advancing CNS drug discovery through integrated models, translational biomarkers, and multidisciplinary expertise to overcome complexity and accelerate therapeutic innovation.
Designing and advancing differentiated small-molecule therapies for obesity and diabetes through integrated expertise, mechanistic insight, and translational strategies.
Inobrodib, an exciting, first-in-class oral anti-cancer drug in clinical development by CellCentric, was collaboratively designed, synthesised and supported on its pre-clinical journey by an integrated project team at Sygnature Discovery. Inobrodib is now showing promising results in Phase I and II trials for multiple myeloma and other cancer types.
Substance Use Withdrawal: How Preclinical Models Inform Treatment Development
Focusing on the withdrawal phase of addiction, this article examines how behavioral pharmacology models assess drug dependence and therapeutic intervention in preclinical studies.
Why Withdrawal is a Critical Phase of Substance Use Disorders
Prolonged exposure to a drug causes the body to adapt, resulting in drug users consuming higher quantities to experience the same effects, a process known as tolerance. When drug exposure is suddenly reduced or stopped, the physiological adaptations lead to withdrawal – a collection of unpleasant and sometimes dangerous symptoms.
A mild version of these symptoms can be observed in heavy caffeine (classified as mildly to moderate addictive) consumers who can be irritable in the morning until they’ve had a cup of coffee. This unpleasant experience can be alleviated by resuming drug use, reinforcing the addictive cycle. As a result, reducing withdrawal severity is a potential target for treating substance use disorders.
Modelling Drug Dependence in Preclinical Studies
It is possible to model how the body adapts to prolonged drug exposure (dependence) and withdrawal in animal models. In contrast to intoxication models, withdrawal studies typically involve non-contingent drug administration, where a scientist administers the drug over an extended period.
When drug administration is abruptly stopped, a characteristic set of symptoms are induced which can be scored using manual observation or by video and behavioral analysis software.
Key Design Considerations
Two critical factors must be carefully controlled when designing a preclinical withdrawal model:
Ensuring sufficient drug exposure to induce dependence
Drug exposure during the dosing phase must remain high enough to induce physiological dependence. This can be achieved in several ways:
Long half-life compounds, where daily dosing maintains sufficient exposure
More frequent dosing schedules for rapidly metabolized drugs
Osmotic pumps, which deliver a continuous dose over days, weeks or months via subcutaneous implantation
2. Ensuring drug exposure is stopped abruptly to trigger withdrawal
To induce this state, drug exposure must be stopped suddenly. This is straightforward for short half-like compounds, where cessation rapidly leads to declining drug levels.
However, challenges arise with long half-life drugs or osmotic pump delivery, where residual drug slowly tapers in the body, preventing overt withdrawal. In these cases, withdrawal can be pharmacologicallyprecipitated by administering a drug that blocks the effect of the first drug. An example is using naloxone to block opioid receptors following morphine exposure.
While precipitated withdrawal can be effective, it introduced additional pharmacology that may not be ideal when assessing novel pharmaceutical treatments.
Using Withdrawal Models to Evaluate Novel Treatments
Preclinical models of dependence and withdrawal can be applied at two stages:
During the dosing phase, to assess whether treatment reduces the development of dependence
During withdrawal, to determine whether a treatment alleviates symptoms
Case Study: Modelling Opioid Withdrawal and Methadone Maintenance Therapy
At Sygnature Discovery, we evaluated whether methadone would prevent rats from experiencing symptoms following prolonged morphine exposure. In the clinic, methadone is used as an opioid maintenance therapy, allowing people that have been using opioids, such as heroin and fentanyl, to transition to a safer opioid without experiencing severe withdrawal. We validated our model with a clinically relevant control so that it can be utilized in assessing efficacy of novel treatments.
To induce dependence, rats were administered with morphine (30 mg/kg) twice a day for 16 days. From day 17, rats were assigned to one of three treatment groups: continued morphine, saline, or methadone (20 mg/kg, twice daily). Throughout both the dosing and cessation phases, body weight, food and water intake were measured daily. In addition, a scientist observed each rat and scored a list of 45 behaviors daily.
Rats that were administered saline during the withdrawal phase consumed much more food (hyperphagia) and water (hyperdipsia) than rats not experiencing morphine dependence. They also showed behaviors that are linked to poor health and stress in rats.
Daily diet and water consumption during baseline (vehicle treatment), induction of dependence (vehicle or morphine treatment) and withdrawal (vehicle or methadone treatment). Red circles highlight morphine withdrawal induced hyperphagia and hyperdipsia. *p<0.05, **p<0.01, ***p<0.001 versus vehicle.
In contrast, rats that were administered methadone during the withdrawal phase did not exhibit hyperphagia or hyperdipsia and behaviors linked to poor health and stress were reduced or absent. Similarly to methadone in the clinic, adverse effects such as decreased respiration were present. These effects are mediated in the clinic by starting treatment at a low dose and slowly increasing to a therapeutic dose.
Overall, these results confirm that methadone reduces opioid withdrawal symptoms in rats similar to the effect seen in humans.
Behavioral observations during morphine dependence (morphine 30 mg/kg, twice daily) or morphine withdrawal, or morphine withdrawal with methadone treatment. Comparisons against vehicle by Wilcoxon Rank Sum test (all p<0.05-0.001). Mean score: +<0.025, ++0.25-0.49, +++0.5-0.74, ++++>0.75.
Explore our addiction research models
This article forms part of a four-part series exploring substance use disorders through the three-phase model of addiction and the preclinical behavioral pharmacology models used to support drug discovery.
Together, these articles examine how addiction develops, why it is so persistent, and how validated in vivo models are used to assess new therapeutic approaches.
Understanding cue-induced relapse using reinstatement paradigms.
Continue the series
Next: Preclinical Models of Substance Use Craving
Focusing on the craving phase of addiction, this article examines how behavioral pharmacology models capture cue‑driven drug seeking and relapse vulnerability.
Addiction research depends on validated in vivo behavioral pharmacology models to assess reward, reinforcement, dependence and relapse-relevant behaviors.
These approaches form part of Sygnature Discovery’s CNS & pain in vivo pharmacology capabilities, supporting translational neuroscience and substance use disorder drug discovery from early research through to clinical decision-making.