## 1 Introduction  
In contrast to industrial applications, automation solutions in life science applications are not yet widespread. The development of automated systems has long been driven by the pharmaceutical industry's need for faster and more efficient drug discovery. A large proportion of fully automated systems are already in use here. In contrast, the automation of classic laboratory processes is still in its infancy. Metrological processes are usually highly automated. Extensive sample preparation processes are often used to ensure optimal separation of the target substances from the surrounding matrices and to protect the analytical devices used from contamination. These sample preparation methods include extractions, centrifugations, purifications, changing the composition of solvents or derivativizations. If compounds are to be determined in biological matrices, additional methods, e.g., for the separation of proteins, may be required. The preparation and processing of samples are still usually performed manually today. On the one hand, this limits the number of samples that can be processed, but on the other hand, personnel is also brought into contact with sometimes dangerous or infectious materials. Due to the repetitive activities, there are also problems regarding work ergonomic issues. The applications that are becoming increasingly important include the determination of \(\Delta\)9-tetrahydrocannabinol (THC) and its metabolites in different biological matrices. THC is the most commonly used drug of abuse [1], and the increasing use of (synthetic) cannabinoids as therapeutic agents, for example, in cancer and pain therapy [2; 3], as well as the trend of using cannabinoids in cosmetics and food lead to an increased need for suitable detection methods [4]. Depending on the aim of the investigation, different matrices, such as blood, serum or plasma, urine, saliva and hair can be used for the quantitative determination of cannabis metabolites. The choice of the matrix depends on the type of possible sampling (invasive/non-invasive) and the detectability/half-life of the analytes in the respective matrix, which is primarily determined by the metabolism of THC. The three primary metabolites are \(\Delta\)9-tetrahydrocannabinol (THC), 11-hydroxy-\(\Delta\)9-tetrahydrocannabinol (THC-OH) and 11-nor-9-carboxy-\(\Delta\)9-tetrahydrocannabinol (THC-COOH). \(\Delta\)9-tetrahydrocannabinol acid A (THCA-A), which occurs naturally in hemp, is converted to \(\Delta\)9-tetrahydrocannabinol by decarboxylation when smoked and is absorbed by the body, where it exerts its intoxicating effects. THC is metabolized in the liver by cytochrome P-450 enzymes into 11-hydroxy-\(\Delta\)9-tetrahydrocannabinol, which is also psychoactive [5; 6]. Oxidation produces the third metabolite commonly used to detect cannabis use, 11-nor-9-carboxy-\(\Delta\)9-tetrahydrocannabinol. THC-COOH is not psychoactive and is glucuronidated and excreted by a phase 2 metabolism in the kidneys [7; 8]. According to this metabolic pathway, saliva is mainly used for the detection of \(\Delta\)9-THC, since the metabolites THC-OH and THC-COOH enter saliva through the mucous membranes only in low concentrations (<0.5 ng/mL) [9; 10] whereas the THC concentration in saliva shortly after inhalation of a cannabis cigarette can be up to 1000 ng/mL [11]. Therefore, saliva is mainly suitable for detecting the just preceding cannabis consumption [12; 13]. Besides THC, mainly THC-COOH is detectable in plasma. Both metabolites are bound to plasma proteins. The high lipophilicity of THC and THC-OH causes the high tissue mobility and subsequent storage of the analytes in the adipose tissue, and at the same time lowers the concentration of the metabolites in the body fluids and enables the long detectability of previous cannabis use due to the gradual release of the stored cannabinoids from the adipose tissue [14; 15; 16].