Maintenance method for a laboratory system comprising a first group and a second group of laboratory instruments for processing biological samples; a plurality of data collection components (20.1, 20.2); and a remote maintenance system communicatively connected to the data collection components (20.1, 20.2); wherein the first group of laboratory instruments is connected to a first data collection component (20.1) while the second group of laboratory instruments is connected to a second data collection component (20.2), the method comprising: - collecting operational data from the laboratory instruments by the data collection components (20.1, 20.2), the operational data being indicative of one or more operational parameters of the respective laboratory instruments; - detecting an anomaly related to one or more of the plurality of laboratory instruments of the first group by the first of the plurality of data collection components (20.1) based on the collected operational data, wherein the first data collection component (20.1) detects anomalies by detecting deviations of the one or more operational parameters from set threshold values; - transmitting context data by the first of the plurality of data collection components (20.1) to the remote maintenance system upon detection of an anomaly, the context data comprising the operational data and data indicative of the anomaly, the operational data having been collected during and before and/or after the anomaly has been detected, and the data indicative of the anomaly comprising test result data of the laboratory instruments generated during and/or before and/or after the anomaly has been detected, wherein sensitive data are filtered out; - determining one or more correlation(s) between the operational data and the anomaly(s) at the remote maintenance system based on the context data, wherein correlation(s) between the operational data and the anomaly(s) are determined automatically using pattern recognition methods; - validating the one or more correlation(s) at the remote maintenance system, wherein the correlation(s) between the operational data and the anomaly(s) are validated by instructing a computer implemented validation engine to validate the correlation(s) between the operational data and the anomaly(s); - determining - at the remote maintenance system - one or more predictive rules corresponding to the validated correlations; - transmitting the one or more predictive rule(s) by the remote maintenance system to the data collection components (20.1, 20.2); - predicting occurrence of an anomaly of one or more of the plurality of laboratory instruments based on the one or more predictive rule(s) by one or more of the plurality of data collection components (20.1, 20.2). - collecting operational data from the laboratory instruments by the data collection components (20.1, 20.2), the operational data being indicative of one or more operational parameters of the respective laboratory instruments; - detecting an anomaly related to one or more of the plurality of laboratory instruments of the first group by the first of the plurality of data collection components (20.1) based on the collected operational data, wherein the first data collection component (20.1) detects anomalies by detecting deviations of the one or more operational parameters from set threshold values; - transmitting context data by the first of the plurality of data collection components (20.1) to the remote maintenance system upon detection of an anomaly, the context data comprising the operational data and data indicative of the anomaly, the operational data having been collected during and before and/or after the anomaly has been detected, and the data indicative of the anomaly comprising test result data of the laboratory instruments generated during and/or before and/or after the anomaly has been detected, wherein sensitive data are filtered out; - determining one or more correlation(s) between the operational data and the anomaly(s) at the remote maintenance system based on the context data, wherein correlation(s) between the operational data and the anomaly(s) are determined automatically using pattern recognition methods; - validating the one or more correlation(s) at the remote maintenance system, wherein the correlation(s) between the operational data and the anomaly(s) are validated by instructing a computer implemented validation engine to validate the correlation(s) between the operational data and the anomaly(s); - determining - at the remote maintenance system - one or more predictive rules corresponding to the validated correlations; - transmitting the one or more predictive rule(s) by the remote maintenance system to the data collection components (20.1, 20.2); - predicting occurrence of an anomaly of one or more of the plurality of laboratory instruments based on the one or more predictive rule(s) by one or more of the plurality of data collection components (20.1, 20.2).